SchoolofBiologicalandChemicalSciencesMScEcologicalandEvolutionaryGenomicsHandbook

KeyFeaturesoftheProgramme

• Gain cutting-edge skills from bioinformatics to fieldwork in a flexible course with many choices

• Teaching from scientists with active research in relevant areas • Optional two week tropical ecology field trip to Borneo • Individual research project supervised by internationally recognised

research scientists • Graduate with a unique combination of expertise

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Contents1.Aims,OutcomesandAssessment 32.ProgrammeStructure: 6TaughtModules 7ResearchProject 143.AcademicCommunity 164.FurtherEnquiries 175.Appendix:DissertationGuide 18

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1.Aims,Outcomes&Assessment1.1.OverallAimsScientiststhathaveskillsinbothgenomeanalysisandecology/evolutionarerareandmuchneeded.Thisprogrammeaimstoproducesuchscientists,openingupcareeropportunitiesinindustryorPhDresearch.Studentshaveachoiceofmodulesthroughoutthecourse,enablingthemtobuildapersonalizedprogramme.Theprogrammewillenableyouto:

• Developasoundknowledgebaseinthefieldsstudied,andkeytransferableskillsintheareasofcommunication,numeracy,informationtechnology,workingwithothers,problemsolving,timeandtaskmanagement

• Developaportfolioofexperimentalskillsandpracticaltechniques,andtherebyprovideyouwiththeconfidencetotacklemoreextendedresearchstudies,perhapsviaaPhD

• Fosteranenquiring,open-mindedandcreativeattitude,temperedwithscientificdisciplineandsocialawareness,whichencourageslifelonglearning

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1.2.LearningoutcomesThisprogrammewillteachtheapplicationofgoodscientificprinciplesinthecontextofindependentandinnovativethought.Youwillbeexpectedtoachieveanadvanced,inter-disciplinaryunderstandingoftechniquesandmethodologiesapplicabletothefieldsofecologicalandevolutionarygenomics,andanappreciationofthecurrentresearchissueswhicharedrivingthisfast-movingfieldforwards.Inparticular,youshouldbeabletodemonstrate:

• Theabilitytosynthesiseinformationwithcriticalawarenessinamannerthatmaybeinnovative,usingexistingknowledgeorcutting-edge,contemporaryprocessesfromtheforefrontofthediscipline

• Alevelofconceptualunderstandingthatwillallowyoucriticallytoevaluateecologicalandevolutionarygenomicresearch,advancedscholarshipandmethodologies,andtoarguealternativeapproaches

• Initiativeandoriginalityinproblemsolving,andbeabletoactautonomouslyinplanningandimplementingtasksataprofessionalorequivalentlevel

• Developskillsinevolutionaryinference,bioinformatics,field-researchandlaboratoryresearch

Fromapracticaltrainingperspective,youwill:

• Acquiretechnicalexpertise,andbeabletoperformtaskssmoothlywithprecisionandeffectiveness

• Beabletoadaptskillsanddesignordevelopnewskillsand/ortechniques,fornewapplicationsthatengagewithuserneeds

StudentstakingthePostgraduateCertificatewillachieveasubstantialsubsetoftheaboveskillsthroughcompletionofthefourcompulsorymodulesinSemesterA,butwillnotcompleteanindependentresearchprojectandthus,willnothavetheexperienceofcombiningalloftheabovetoproduceathesis.

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1.3.Teaching,learningandassessmentstrategiesThemodulesmakinguptheprogrammewillbetaughtinblocksoftwoweeks,withasubsequentweekforindependentlearningandcompletionofcontinuousassessmentexercises.Mostmodulescompriselecturesduringthemorningofeachdayandthentheafternoonsarededicatedtoseminars,breakoutdiscussiongroups,workshops,andlaboratoryorcomputer-basedpracticals.MuchofthetheorygleanedfromformalteachingduringthemodulesinSemesterAwillbeplacedin'real'contextontheresidentialfieldcourseinBorneo,whichwillcomprisesitevisits,aswellasresearchpresentationsfromscientistsandstakeholders.Thecoursealsoincludesagroupproject,inwhichteamsofstudentswillanalysealargegenomicdataset.ThesecondhalfoftheMSccourseconsistsofasubstantialindependentresearchproject,whichwillconsolidateandutilisethetheoretical,practicalandtransferableskillstaughtbythepreviousmodules.OutlineofassessmentfortheawardofMScCoursework(50%offinalgrade):Taughtmoduleswillbeassessedusingavarietyofassessmentmethods(reports,essays,practicals,presentations,MCQs).Eachmoduleisweightedat8.33%ofthefinalassessmentload.Dissertation(50%offinalgrade):Theexaminationoftheresearchprojectisviaacombinationofdissertationthesis(80%)andapresentation(20%).Alltaughtmodulesandthedissertationmustbepassedat50%forawardoftheMSc.

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2.ProgrammeStructureTheprogrammeisstructuredtoallowlogicalprogressionthroughthevariousmodules.InSemesterA,studentswilltakefourthree-weekmodules(4x15credits).InSemesterBstudentstakeonefurtherthree-weekmodule(15credits)andaninternationalfieldcourse(15credits).Fortheremainderoftheprogramme,studentsengageinacutting-edgeresearchproject(90credits),apieceofindependentandnovelresearchthatshoulddrawuponmanyoftheaspectstaughtandtheskillsexperienced.Youareencouragedtousetimetabledindependentstudytimetoengagewithcurrentresearchersinlabs,orvolunteerforfieldworkassistance,therebyexposingyourselftotheday-to-dayexperienceoftheresearchenvironment.Youareencouragedtoattendlabspecificmeetingsalsoandgainafullunderstandingofthebreadthofresearchavailablebeforemakingachoiceforyourownspecificproject.

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2.1Taughtmodules:SemA-BIO721PGenomeBioinformatics–15creditsThisisacompulsorymodule.ThismoduleissharedwiththeMScinBioinformaticsModuleOrganiser:DrYannickWurmThismoduleprovidesanintroductiontobioinformatics,focusingspecificallyontheanalysisofDNAsequencedata.Lecturescoverthebioinformaticsmethods,algorithmsandresourcesusedfortaskssuchassequenceassembly,genefindingandgenomeannotation,phylogenetics,analysisofgenomicvarianceamongpopulations,genomewideassociationstudiesandpredictionofgenestructureandfunction.Practicalexercisesareusedtogainexperiencewithrelevantexistingbioinformaticstools,dataformatsanddatabases.Theaimofthismoduleistointroducethefieldofbioinformatics,withaspecificfocusontheanalysisofDNAsequencedata.Boththeoreticalandpracticalcomputingaspectsarecovered.Apriorunderstandingofbasicbiologyandgeneticsisassumed.LearningoutcomesOncompletionofthismoduleyoushouldbeableto:1.Defineandexplainconceptsingenomeanalysis,suchasgenomeassembly,sequencealignmentandgenomewideassociationstudies.2.Demonstrateawarenessofkeypubliclyavailablebioinformaticsresources(analysistoolsanddatabases)usedforgenomeanalysis.3.Identifyandutiliseappropriatepubliclyavailablebioinformaticsresourcestoperformgenomeanalysistosolvebiologicallyrelevantproblems.4.Comprehendtheongoingchallengesofgenomeanalysis.5.Demonstratetheabilitytoclearlyandsuccinctlyexplaincomplexgenomeanalysisworkflowsinawaythatiscomprehensibletobiologists.Readinglist:IntroductiontoBioinformaticsbyArthurLeskBioinformaticsforBiologistsbyPevzner&ShamirExploringPersonalGenomicsbyDudley&Karczewski

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SemA-BIO723PCodingforScientists–15creditsStaff:FabrizioSmeraldiThisisanoptionalmodule,thealternativebeingBIO737P.ThismoduleissharedwiththeMScinBioinformaticsThismoduleprovidesahands-onintroductiontocomputerprogramming(popularlyknownas"coding"),primarilyusingthepopularPythonscriptinglanguage.Thefocusisonproducingrobustsoftwareforrepeatabledata-centricscientificwork.Keyprogrammingconceptsareintroduced,andtheseconceptsarethenbroughttogetherinscientificallyrelevantapplicationstoanalysedata,interactwithadatabaseandcreatedynamicwebcontent.Goodcodingpractice,suchastheimportanceofdocumentationandversioncontrol,isemphasisedthroughout.Themodulesaimstointroducecodingtostudentsfromanaturalsciencesormedicalbackground.Theemphasisisonpracticalskillsneededtocreaterobustandwell-documentedsoftwareforconductingrepeatabledata-centricscientificwork.Noparticularcomputingskillofspecificscientificknowledgeisrequiredtofollowthismodule,butabasiclevelofcomputerliteracyandscientificunderstandingisassumed.Learningoutcomes Oncompletionofthismoduleyoushouldbeableto:1.Defineandexplainkeyprogrammingconceptssuchasvariables,filehandlingandconnectivitytoexternalresourcesviaapplicationprogramminginterfaces(APIs).2.Utilisetheaboveknowledgeofprogrammingconceptstoproducefunctioningprogramsusingascriptinglanguage.3.Demonstrateawarenessofgoodcodingpractices,suchasunittesting,versioncontrolanddocumentation.4.Designandimplementprogramcodetoimplement,simplifyorautomatebiologicaldataanalysistasks.5.Utiliseexternalresourcessuchascodelibraries,databaseandwebservicestoaddfunctionalitytoprogramcode.6.Demonstrateaprofessionalandresponsibleapproachtosoftwaredevelopmentbyfollowinggoodcodingpractice.ReadingListBuildingBioinformaticsSolutionsbyConradBessantetal.ProgrammingPythonbyMarkLutzProgrammingRubybyDaveThomasetal.

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SemA-BIO737PEcosystems:Structure&Functioning–15creditsThismoduleissharedwiththeMScsinAquaticEcologybyResearch,theMScinEcologyandEvolutionaryBiologyandtheMScinFreshwaterandMarineEcology.Staff:BethClare,AndrewHirst,MarkTrimmer,PavelKratinaWhilewehavelongappreciatedthestructureofecosystems,theimportanceofecosystemfunctioninghaslaggedbehindsomewhat.Thismoduleaimstoredressthebalancebyexploringtheuseofmoderntools,whichallowustothoroughlyintegratemeasuresofecologicalstructureandfunctioning.AspectsoftheMetabolicTheoryofEcology,body-sizerelationships,stableisotopeanalysisandDNAbar-codingwillallbecoveredinrelationtotopicssuchasphotosyntheticandchemosyntheticprimaryproduction;theimpactsofinvasivespecies;aquatic-terrestriallinkagesandcrossecosystemboundarysubsidies;biogeochemistryandnutrientdynamics;planktondynamicsandorganismalphysiologyinachangingworld.ReadingEcologicalMethodologybyC.JKrebsSemA-BIO781PStatistics&Bioinformatics–15creditsStaff:RobKnell,SteveLeComber,YannickWurmThismoduleissharedwiththeMScsinBioinformatics,EcologyandEvolutionaryGenomics,AquaticEcologybyResearch,FreshwaterandMarineEcology,andPlantandFungalTaxonomy,DiversityandConservation.Themoduleprovidesyouwithanessentialtraininginexperimentaldesign,datahandlinganddataanalysesinacontextappropriateforenvironmentalandevolutionarybiology.Themodulewillestablishasolidfoundationfrompreviousknowledge,andthenprogresstomoreadvancedmethods.Thecoursefocusesonhowtoselecttheappropriatemethodofanalysis,howtoanalysedatausingthestatisticalprogramminglanguageRandhowtointerprettheoutputofthatanalysis.Thefirsthalfofthemodulewilldealwithparametricstatisticsincludinggeneralandgeneralizedlinearmodels,andthesecondhalfwillmoveontomultivariatestatisticsandthebasicsofBayesiananalysis.ReadingListIntroductoryR-RobKnellhttp://www.introductoryr.co.uk

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SemA-BIO731PResearchFrontiersinEvolutionaryBiology–15creditsStaff:RichardBuggs,RichardNichols,SteveRossiter,AndrewLeitch.Guestlecturers:JamesShapiro(U.Chicago),IliaLeitch(RBGKew),RichardBateman(RBGKew)Wewillexplorethefrontiersofresearchinevolutionarybiology.Topicscoveredwillinclude:genetreesversusspeciestrees,phylo-genomics,neutralversusselectiveforces,molecularconvergence,theoriginofangiosperms,theevolutionofsociality,thesignificanceofwholegenomeduplicationandhybrid-isation.Currentmethodsbeingusedtotackletheseareaswillbetaught,withanemphasisonDNAsequenceanalysisandbioinformatics.Whereasundergraduatedegreescommonlyfocusonwhatweknow,thisMaster’smodulewillshiftthefocusontowhatwedon’tknow.Youwilllearntoaskrelevantquestions,anddesignapproachestoseekinganswerstothosequestions.ThismodulewillincludeadayatRoyalBotanicGardens,Kew.ReadingListEvolution-Bartonetal.,ColdSpringHarborLaboratoryPress,2007TheOriginsofGenomeArchitecture-Lynch,Sinauer,2007BigQuestionsinEcologyandEvolution-SherrattandWilkinson,OUP,2009LifeAscending:The10GreatInventionsofEvolution-NickLane,Norton/Profile2009SemBBIO725P–Post-genomicBioinformatics-15creditsThisisanoptionalmodule,thealternativebeingBIO731P.ThismoduleissharedwiththeMScinBioinformatics.Staff:ConradBessantThismoduleprovidesanintroductiontobioinformatics,focusingspecificallyonthemanagementandanalysisofdataproducedbyso-calledpost-genomicmethodssuchastranscriptomics,proteomicsandmetabolomics.Lecturescoverthebioinformaticsmethods,algorithmsandresourcesusedfortaskssuchastheidentificationandquantitationoftranscripts,proteinsandmetabolites,andanalysisoftheinteractionsbetweenthesekeybiologicalmolecules.Practicalexercisesareusedtogainexperiencewithbioinformaticstools,dataformatsanddatabasesthathavebeendevelopedforthisfield.Theaimofthemoduleistointroducethespecificaspectsofbioinformaticsthatrelatetolarge-scalepost-genomicdatasetsproducedbybioanalyticalmethodssuchasRNA-seqtranscriptomics,proteomics,metabolomicsandvariousmethodsfor

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characterisingmolecularinteractions.Priorknowledgeofbasicmolecularbiologyandbiochemistryisassumed.LearningoutcomesOncompletionofthismoduleyoushouldbeableto:1.Explainthemethodsusedtogeneratepost-genomicdata.2.Defineandexplainconceptsinpost-genomicdataanalysis,suchasidentificationandquantitationofbiologicalmoleculesandtheusetostatisticstoextractbiologicalinsightsfromthisinformation.3.Demonstrateawarenessofkeypubliclyavailablebioinformaticsresources(analysistools,databasesanddatastandards)usedforpost-genomicdataanalysis.4.Identifyandutiliseappropriatepubliclyavailablebioinformaticsresourcestoperformpost-genomicdataanalysistosolvebiologicallyrelevantproblems.5.Comprehendtheongoingchallengesofpost-genomicdataanalysis.6.Demonstratetheabilitytoclearlyandsuccinctlyexplaincomplexpost-genomicdataanalysisworkflowsinawaythatiscomprehensibletobiologists.Readinglist:BioinformaticsforOmicsDatabyBerndMayerProteomeBioinformaticsbySimonHubbardandAndrewJones

SemB-BIO733PEcological&EvolutionaryGenomicsGroupProject–15creditsThisisacompulsorymodule.Staff:RichardBuggsThemoduleprovidesanopportunitytofurtherdevelop,andintegrate,theskillsacquiredintheprecedingfourmodules(genomics,post-genomics,statistics,codingandevolutionarybiology)oftheMScprogrammewhilesimultaneouslygaininghighlydesirabletransferableskillsingroupworkingandcommunication.Inthismodule,studentsareorganisedintosmallteams(~3-4membersperteam).Eachteamisgiventhesamegenomicortranscriptomicdatasetthatmustbeanalysedbytheendofthemodule.Eachteammustdesignanappropriateanalysispipeline,withspecifictasksassignedtoindividualteammembers.Theprojectinvolveselementsfromthepreviousbioinformaticsmodules(genomics,post-genomics,codingandstatistics)aswellasnewtopicsthatareintroducedduringthemodule.Thismoduleservesasasimulationofarealdataanalysisenvironment,providinginvaluableexperienceforfutureemployability.

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SemB-BIO792PEcology&EvolutionaryBiologyfieldcourse–15credits(residentialfieldcourseinBorneo)Thisisanoptionalmodule,thealternativebeingBIO793P.ThismoduleissharedwiththeMScinFreshwaterandMarineEcologyandtheMScinEcologyandEvolutionaryBiology.Staff:StephenRossiter,RobKnellThemodulewillbeconductedover12daysatDanumValley,Sabah,Malaysia.Topicswillincludeacharacterizationofthefoodwebofthehumiclystainedandhydrologicallyunstablepeatswamplakeandflashyrainforestrivers,adaptationsexpressedbyfishinsuchwaters,impactsofcatchmentcharacteristicsontheecologyofaquaticorganisms,andpotentialthreatstotropicalforestsandlakes.Therewillalsobesomeriparianecologyforbalance:thecharacteristicsoftropicalrainforests,adaptationsintropicalplants,processessuchaspollination,seeddispersal,herbivoryanddecomposition.Conditionscanbetoughintermsofhumidityandtemperatureandsoparticipantsshouldbereasonablyfit.Fieldworkwillbeconductedonfoot,bykayak,andbyswimming!Duetothenatureofthefieldworkonthismodule,itmaynotbesuitableforstudentswithsomeongoingmedicalconditions.AnystudentwithsuchconditionsinterestedinthismoduleshoulddiscussitwiththeSBCSStudentSupportOfficer.Intheeventthatitisnotpossibletomakesuitableaccommodationsitmaybenecessarytochooseanalternativemodule.ReadingListCorlettR(2009)TheEcologyofTropicalEastAsia,OxfordUniversityPress,OxfordDudgeonD(Ed.)(2008)TropicalStreamEcology,AcademicPress,LondonKricherJC(2011)TropicalEcology,PrincetonUniversityPressOsbornePL(2012)TropicalEcosystemsandEcologicalConcepts,CambridgeUPPrimackRB&CorlettR(2005)TropicalRainForests:AnEcologicalandBiogeographicalComparison,Blackwell,Malden,MASodhiNS,BrookBW&BradshawCJA(2007)TropicalConservationBiology,Blackwell,Malden,MAWhitmoreTC(1998)AnIntroductiontoTropicalRainForests,OxfordUP

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BIO793PCretefieldcourse–15credits(residentialcourseinCrete)Thisisanoptionalmodule,thealternativebeingSBSM030.ThismoduleissharedwiththeMScinEcologyandEvolutionaryBiologyStaff:ArisMoustakasOnthisfieldcoursewewillexploretheuseofstatisticalmethodologyindesigning,collecting,analyzing,interpreting,andpresentingpopulationdynamicsexperimentsandobservations.Wewillcoverelementsofexperimentaldesign,hypothesistestingandstatisticalinference,analysisofvariance,correlation,andup-to-dateregressiontechniques.ThroughoutthecoursetheapplicationofstatisticaltechniqueswithinabiologicalcontextwillbeemphasizedusingdatathatwillbecollectedinthefieldmergedtogetherwithlargerdatasetsavailablefromtheNaturalHistoryMuseum,Crete.Furtheronsitevisitstorarespeciesandrarehabitatswillbemade,linkingpopulationdynamicsproblemswithpracticalissuesinconservationbiology.ReadingListBlondel,etal.TheMediterraneanRegion:BiologicalDiversityinSpaceandTime,OxfordBiology,2010Matloff.TheArtofRProgramming:ATourofStatisticalSoftwareDesign,NoStarchPress,2011QuinnandKeough.ExperimentalDesignandDataAnalysisforBiologists,CambridgeUniversityPress,2002

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2.3IndividualResearchProject(Dissertation)SemB&SemC-BIO704PEcological&EvolutionaryGenomicsIndividualResearchProjectThisisacompulsorymodule.Staff:Projectsofferedbydifferentstaffaccordingtostudentresearchinterestsandexpertise.Thismoduleinvolvesanovelpieceofresearch,typicallyanalysingagenomic,transcriptomicorproteomicdatasetcollectedinanecologicalorevolutionarycontext.Thismoduleistheculminationoftheformalandtheoreticaltraininginthelecturetheatreorseminarroom,allowingstudentstodeveloptheirbioinformaticandscientificskills.Thismoduleprovidesanopportunitytofurtherdevelopandapplyskillslearnedduringthepreviousmodules,byconductinganovelpieceofgenomeanalysiswork,typicallywithinanactiveresearchgroupeitherwithinQMULoratpartnerorganisation.Thespecificnatureofeachprojectwillbedeterminedthroughdiscussionsbetweenthestudent,thecourseorganiserandtheprojectsupervisorbutwillalwaysinvolvedataanalysisand/orsoftwaredevelopmentinacuttingedgeareaofbiologicalorbiomedicalresearch.ThisservesasexcellentpreparationforfutureemploymentorPhD.MostprojectsareofferedtostudentssothattheycanbenefitfromclosealignmentwithcurrentPhDorpost-doctoralresearchwithinspecificresearchgroups,bothatQMULorinpartnerinstitutionswithinLondon.Thediversityofexpertiseoflecturersinvolvedwiththeprogrammemeansthatgoodsupervisioncanbefoundforabroadrangeofstudiesinecologyandevolutionarygenomics.DissertationsmaybeundertakenwiththeassistanceandguidanceofrelevantexternalorganisationswiththeprovisothatasuitableSBCSsupervisorisalsoidentified.Thedissertationaimstomakeanovelcontributiontoscientificknowledge.Itshoulddemonstratefamiliaritywiththerelevantliteraturetowhichtheresearchcontributes.Inundertakingsuchanextensiveproject,studentsareexpectedtodemonstrateasoundunderstandingofprojectdesign,samplecollection,dataanalysis,andtheabilitytoproduceacoherentandwellstructuredpieceofwrittenreporting.DuringSemesterA,studentswillbeencouragedtotalkwithpotentialsupervisorsand‘shadow’currentPhDstudents.FromFebruarythroughtotheendofJuly,studentsshouldbeundertakinglaborbioinformaticswork,andthenwritingupinAugustforanearlySeptembersubmission.AtthebeginningofAugust,eachstudentwillprepareandgivearesearchseminarbasedupontheirworktoanaudienceofstaffmembers&peers,duringwhichtherewillbeplentyoftimeforquestions.

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Examplesofprojects:

• Thestudyofsensorygenesinecholocatingbatsandwhales• Identifyingthegenesandevolutionarymechanismsinvolvedintheevolution

ofsocialbehaviour• Bioinformaticanalysesoftreegenomes• Thesystematics,phylogenyandphylogeographyofneotropicalbatsanduses

molecularmethodsfordietaryanalysis• Effectsofnitrogen&phosphorusongenomeevolutioninangiosperms• Theevolutionofgiantgenomes

Forfurtherdetailsoftheresearchinterestsofthepotentialsupervisorsabove,pleasevisittheAcademicStaffwebpagelinksfromtheSBCSOrganismalDivisionhomepages:http://www.sbcs.qmul.ac.uk/about-us/researchdivisions/index.htmlOrfollowourexploitsviaTwitter:@QM_EcoEvo

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3.WiderParticipationintheAcademicCommunity3.1.LinkswithotherQMULMSccourses:ThisMScprogrammehasoneormoresharedmoduleswiththefollowingMScprogrammestaughtbytheSchoolofBiologicalandChemicalSciencesatQMUL:

• AquaticEcologybyResearch• FreshwaterandMarineEcology• EvolutionaryandEcologicalGenomics• Bioinformatics• PlantandFungalTaxonomy,DiversityandConservation

3.2.SciencelecturesinLondon:StudentswillalsobeabletoattendotherrelevantlecturesinLondonaspartofseveraldifferentseminarprogrammesincludingthoseofthe:

• QMULSBCSOrganismalBiologyseminarseries• LondonCentreforEcologyandEvolutionhttp://www.ceevol.co.uk• LondonEvolutionaryResearchNetworkhttp://londonevolution.net

Aprogrammeofrelevantlecturesiscommunicatedbye-mailwithregularupdates.News&viewsarealsoexpressedviaTwitter:followuson@QM_EcoEvo3.3.Facilities:HighPerformanceComputerFacilityGenomicsresearchersatQMULusetheUniversity’shighperformancecomputercluster,whichincludeselevenlargenodeseachcontaining48coresand512GBofRAMand1272Westmerecores(106nodes),eachwith24GBRAM.SBCSmembersroutinelyusetheUniversity'ssecondHPCcluster,fundedbytheUK-wideGridPP,containingover1400multi-coreCPUs.GenomicsLaboratoriesStudentswillhaveaccesstonewlyrefurbishedgenomicslaboratoriesintheFoggBuildingontheMileEndCampus,andattheGenomeCentreattheCharterhouseSquarecampus.Thesecontainstate-of-the-artequipmentforworkfromnucleicacidextractionthroughtosequencedatageneration.

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4.FormoreinformationonaspectsoftheEcologicalandEvolutionaryGenomicsMScProgrammeAnapplicationpackandfurtherinformationonfees,financialsupportandstudyingatQMULcanbeobtainedfromtheaddressbelow:PostgraduateAdmissionsSchoolofBiologicalandChemicalSciencesQueenMary,UniversityofLondonMileEnd,LondonE14NSTel:02078823328Fax:02089830973e-mail:sbcs-pgadmissions@qmul.ac.ukOrvisitthewebsiteThisbookletprovidesinformationforthoseinterestedintheMScEcologyandEvolutionaryBiology.Whileeveryefforthasbeenmadetoensurethattheinformationinthishandbookiscorrectatthetimeofgoingtopress,theSchoolcannotberesponsibleforanyerrorsitcontains.TheSchoolreservestherighttocancelormakeadjustmentstothespecificationsofparticularmodulesifnecessary.

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5.AppendixQueenMary,UniversityofLondonMScGuidelinesforthePreparationandSubmissionofaDissertationAdissertationformsanintegral,assessedcomponentoftheMSc.Itshouldreporttheresultsofanoriginalpieceofresearch,whichincludesfieldworkand/orlaboratoryanalysesonatopicrelevanttotheMSccoursesyllabus.Dissertationsshouldinclude:(i)aclearstatementandexplanationoftheproblembeingexamined(ii)relevantbackgroundinformation,includingaconciseliteraturereviewandevaluationofproposedmethodology(iii)detailsofthedatacollectedandthevariousanalysescarriedout(iv)interpretationofresults(v)discussionofthewidercontextandrelevanceoftheresults(vi)conclusion(s).Thewrittentextshouldbesupplementedbyappropriatetables,maps,diagrams,photographsandotherillustrativematerial.PreparationoftheDissertationDissertationsmustconformtothefollowinglayout.FormatDissertationsshouldnotbemorethan10000wordsinlength,exclusiveofReferencesandAppendices.Youareadvisedthatconcisenessisadesirablequalityinproducingascientificreportandthatyourabilitytowriteconciselywillbeassessedcarefully.Areportinexcessof10000wordsmayleadtolossofmarks.Checkafewpapersinarecentissueofarespectedjournal(e.g.FreshwaterBiology)forfurtherguidance.PagesizesforthedissertationaretobeA4.Dissertationsmustbetyped,usingfontsize12,preferablyinTimesNewRoman,andtextisusuallyneaterwhen1.5orevendoublespaced.Notethatonlyonesideofasheetshouldbeusedfortextorillustrativematerial.Toallowforbinding,theleftmarginshouldbe3.5cmanda2.5cmrightmarginisrecommended.Allpagesmustbenumbered.Preliminarypages(TitlethroughtoListsoffiguresetc.,seebelow)shouldbeseparatelynumberedusingRomannumerals.NumberofcopiesTWOcopiesarerequired,bothofwhichshouldbeboundusingcombbindersandhaveafrontcoverasonpage10;adeclarationform(similartopage11)shouldalsobecompletedandsubmittedwithyourthesis(awordversionwillbemailedtoyounearerthetime).Owncopieswillbeadditionaltothetwosubmitted.

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Elementstobeincluded(logicallyinthisorder)TITLEPAGE-statingthefollowing:(i)Thetitleofthedissertation(ii)Yourname(ii)Theyearofsubmission(iii)Thefollowingstatement:‘ThisresearchdissertationissubmittedfortheMScinEcologicalandEvolutionaryGenomicsatQueenMary,UniversityofLondon’DECLARATION–thatthedissertationisyouroriginalwork,specificallypreparedforthefinalexamination(formattheendofthisdocument)ABSTRACTofnomorethan400words,plusastatementoftheNUMBEROFWORDSinthetextACKNOWLEDGEMENTSLISTOFCONTENTS–givingpagenumbersforsectionsLISTOFFIGURES–givingpagenumbers(thisincludesmaps)LISTOFTABLES–givingpagenumbersLISTOFPLATES–givingpagenumbersMAINTEXT–consistingofIntroduction,Aims,Studysites,MaterialsandMethods,Results,DiscussionandConclusions(ordercanbemovedaroundasappropriate)TheIntroductionusuallyoutlinesthescientificproblemandapproach,andshouldincludeaconciseliteraturereviewlogicallyleadingintoandframingthestudy–tryandidentifytheresearchgapsthatyouareintendingtofill.Aimsshouldbeconcise.Resultsshouldbeconcise,descriptiveandshouldnotentaildetaileddiscussionofwhattheymaymean.Discussionshouldinterprettheresultsinrelationtotheinitialstudyaimsandshouldsettheminthewidercontext.Thissectionshouldalsoincludesomecriticalcomparison.Conclusionsshouldbeaconcisesummationoftheapproachundertakenandmainfindingsofthestudy.Inthissectionitmayalsobeappropriatetoprovideanautocritiquedetailingperceptionsofthestrengthsandweaknessesofthestudy.LISTOFREFERENCES–shouldconformtothesystemadoptedinthejournalFreshwaterBiologyi.e.theHarvardsystemAPPENDIX/APPENDICES–ifnecessary

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Dissertations:Whatdoyouwanttoachieve?ManystudentsinitiallyviewthesuccessfulproductionoftheirdissertationasnothingmorethananessentialpartoftheprocesstoobtainanMSc.However,yourdissertationcanbethekeytomuchmorethanthis.InadditiontoyourMScdegree,itcanprovidebeneficialopportunities.Itisimportantthatyouconsiderthesepotentialbenefitscarefullyduringtheplanningofyourproject.Yourprojectandtheresultingdissertationcanprovidethefollowingopportunities:1)Chancetoacquirenewskillsandbroadenyourhorizons.YourMScisamulti-disciplinarysubjectandyouarelikelytoobtaingreaterintellectualsatisfactionandimproveyouremploymentpotentialifyouuseyourprojectasanopportunitytoacquirenewexpertise.Consideratopicthatrequiresyoutousenewskills,ratherthanonethatmerelyusestheskillsdevelopedwhenyouwereanundergraduate.Chooseasubjectthatisrelativelynewtoyouandwhichwillextendyourknowledgeintoanewareaofexpertise.Youhaveauniqueopportunitytoobtainassistancefromsupervisorswithexpertiseinseveraldisciplines.2)Aimtogetyourdissertationpublishedinascientificjournal.MostMScdissertationsaresubstantialpiecesofworkandmanyarepotentiallysuitableforpublication.Justalittleextrathoughtduringthepreparationofyourprojectandsomeadditionalcareinwriting-upcanmakeyourdissertationpublishable.Yoursupervisormaybeabletoofferconsiderablehelpinthis.Iftheymakeasignificantcontributiontothedevelopmentofyourproject,methodsofdatacollectionandanalysis,orediting,itisreasonabletoconsiderjointpublication(youwouldnormallyexpecttobefirstauthor).ThefollowingexamplepublicationshavearisenfromFACS&AERMScprojects(student;supervisor):-Kibriya&Jones2007NutrientavailabilityandthecarnivoroushabitinUtriculariavulgaris.FreshwaterBiology53:500–509Woodward&Layer2007PatternandprocessintheLochnagarfoodweb.DevelopmentsinPaleoenvironmentalResearch231-252Rawcliffe,Sayer,Woodward,Grey,Davidson&Jones2010Backtothefuture:usingpalaeolimnologytoinferlong-termtemporalchangesinshallowlakefoodwebs.FreshwatBiol55:600-613.Ravinet,Syvaranta,Jones&Grey2010Fishexploitationofmethane-derivedcarboninatemperatelakesystem.Oikos119:409-416.Dossena,YvonDurocher,Grey,Montoya,Perkins,Trimmer&Woodward2012Warmingalterscommunitysizestructureandecosystemfunctioning.ProcRoySocB3)Establishkeycontacts,perhapswithpotentialemployers.Ifyouundertakeaprojectinconjunctionwithaspecificexternalagency,usetheopportunitytodevelopusefulcontacts.Bydeliveringacompetentandprofessionalreportintheformofyourdissertation,youmayimpresstheagencythatyouworkedwithtothe

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extentthattheymaybeabletoconsideryouasafutureemployee.Youruniversitysupervisorsarealsolikelytouseyourprojectworkasaguidetowritingagoodreferenceonyourbehalf.4)Experiencenovelsituations.Providingyouhavetheconfidenceandskillstodeliveracompetentpieceofworkinanovelsituation,youcanconsideraprojectthatwillrequireyoutoworkinanecosystem,contextorcountrythatisnewtoyou.TherearecertainrisksinvolvedinworkingremotefromLondon,buttherewardsfromthesuccessfulcompletionofadissertationinanewand/ordifficultenvironmentcanbeconsiderable.Closeliaisonwithapotentialsupervisorisessentialifyouareconsideringthispossibility.Itisfartooeasytobeover-ambitiousandyouneedtobeveryflexibleifyourinitialplansproveunworkableonceyouarriveatyourstudysite.TypesofMScProjectIngeneral,therearefourtypesofprojectthatyoucouldconsiderforyourMScdissertation:a)Projectofyourowndesign.Weencouragestudentstodesignandinitiatetheirownprojectbutreservetherighttorequiremodificationofproposalsthatareover-ambitiousorappearunworkable.Agoodprojectofthistypecandemonstratethatyouhaveconsiderableinitiativebutitisimportanttoensurethatyouarestillguidedbyyoursupervisor.b)Commissionedproject.Thereareoftenprojectsonofferthatareencouraged/commissionedbyexternalagenciesorrelevantNGOs.Thesehavetheadvantageofgivingyouexperienceofareal-worldsituationandthesatisfactionofknowingthatagoodreportwillbeputtousebythecommissioningagency.Yourworkwillbelikelytoprovideasoundguidetoafutureemployer.Theremayalsobesomefinancialsupportforsuchprojects.c)Projectalignedtostaffresearch.StaffteachingtheMScshavetheirownresearchprogrammesandmostwillbeabletoidentifyworkthatcanpotentiallybeundertakenasadissertation.Thistypeofprojectmaywellleadtoapublishedpaperandtheworkwillbeclearlymanageableasanindividualproject.Byundertakingworkthatispartofalargeroveralleffortyouarelikelytoacquirenewskillsandbeabletogointoconsiderabledepthinyourstudy.d)Projectthatincludesanelementofadventure.Ifyouchoosetoworkataremoteordifficultsite(e.g.outsideEurope)youmaymakeyourprojectadventurousbuttherearerisksattached.Projectsinremotelocationshaveoftenproducedratherpoordissertationsbecauseofunanticipateddifficulties.However,whenthestudentundertakingaremoteprojecthasshownconsiderableskillindealingwithaproblematicalsituation,themarksawardedhavesometimesbeenexcellent.

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Whatevertypeofprojectyoudecideupon,trytomaintaingoodcontactwithyoursupervisorwheneverpossible.AlsorememberthatallstaffassociatedwiththeMScFreshwaterandCoastalSciencescoursemaybewillingtoprovideadviceatanystageduringyourproject,particularlywhenyouareplanningwhereyouwillworkandwhatyouwilldo.Dissertations:SupervisionbypersonswhoarenotmembersofQMULstaff1.TheappointmentassupervisorsofdissertationsforMaster’sprogrammesofpersonswhoarenotmembersofthestaffofQMULandmaybebasedoverseasissubjecttoanumberoftermsandconditionswhicharesetoutbelow.2.WhereaMaster’sstudent’ssupervisorisnotamemberofQMULstaff,thefollowingrequirementsmustbemet:

• Departmentsareresponsibleformaintainingadequateandappropriateprojectsupervisionandformonitoringthatsupervision,especiallywhereastudentisspendingpartormostofthetimespentontheprojectoutsideQMUL.

• Thecurriculumvitaeofanysupervisorproposedandhis/hersuitabilityasasupervisormustbeconsideredbytherelevantBoardofExaminersbeforehe/sheisformallyappointed.

• AsecondsupervisorwhoisamemberofstaffofQMULmustbeappointedwithresponsibilityformonitoringthestudent’sprogressandthelevelofinput/directionthestudentisreceivingfromthenon-QMULsupervisor.

• ThesecondsupervisormustmaintainregularcontactwiththesupervisorwhoisoutsideQMULandshouldcollaboratewithhim/herintheoveralldirectionofthestudent’sproject.

• Thesecondsupervisormayberequiredtotakeonmorethanthenormalsupervisionexpectedofasecondsupervisor.

• IntheeventofanyproblemwiththesupervisionbeingprovidedbythesupervisorfromoutsideQMUL,thesecondarysupervisorwillconsultthedepartment’sGraduateTutoronactiontobetaken.

Dissertations:OrganisingyourProjectTopicManydifferenttopicsaresuitable.Aglanceatthetitlesofrecentdissertationswillgiveyouanideaoftherangeofsubjectsstudied.Mostaresite-basedorproblem-orientated.Allshouldbeoriginalpiecesofworkandusuallyinvolvethecollectionofquantitative/qualitativedata.Unlessyouarecertainthatyouwishtopursueaparticularspecialisationinyourfuturecareer,itisusefultotakethisopportunitytobroadenyourexperienceoftheMScbystudyingatopicthatisrelativelyunfamiliartoyou.

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WorkingaspartofalargerprojectIfyouundertakeyourprojectworkinassociationwithanexternalorganisation,youwillsometimesbeaskedtodoworkthatwillcontributetoateamproject.Thisisallright,providingyouworkindependentlyandanyjointstudiesthatmaybeincludedinyourdissertationareclearlyindicatedassuch.However,wedoexpectyoutoshowinitiativeindevelopingyourproject,soitisunsuitabletodoonlyroutinestudiesaccordingtoamethodologythathasbeenworkedoutindetailbyothers.Ifsuchstudiesformapartofyourresearch,thenweexpectyoutoalsoincludeasubstantialsectioninyourdissertationthatevolvedfromyourown,independentideas.ScheduleYouwillnormallybeabletobeginfulltimeworkonyourprojectinlateApril,dependinguponprogramme.However,itisnevertooearlytobegintoplanwhatyouwillstudyforyourproject.Inthepast,somestudentshavedevelopedprojectsfromideasandcontactsmadeduringSemesterA.Moststudentsplantheirprojectduringthespringterm.IfyouareseekingtoworkwithanexternalorganisationitisagoodideatomakeaninitialapproachtothemsoonafterChristmas.Nevertheless,someexcellentprojectshaveresultedfromplansthatwereinitiatedaslateasMay!LocationFieldworkisusuallyundertakeninGreatBritain.However,wearepreparedtoconsiderprojectsbasedintheEuropeanUnionorbeyond,providedadequateprovisioncanbemadeforsupervision.Youshouldbearinmindthat,ifyoursupervisorisnotabletovisityouinthefield,becauseyoursiteisremotefromLondonorveryexpensivetoreach,youareunlikelytogetQMULguidanceinthefieldshouldanythinggowrong.SafetyAfullriskassessmentmustbecarriedoutinkeepingwiththeQMULprocedureinthisrespect,particularlyfocusingonaspectssuchasinterviews,fieldwork,laboratorywork,lonework,etc.Thisriskassessmentmustbeundertakenincollaborationwithyoursupervisor.FundingSomeprojectseachyeararepartfundedbyexternalorganisationsthatrequireaparticularpieceofworktobedone.Itisimpossibletopredictinadvancehowmanysuchprojectswillbeonofferinaparticularyear.Thecoursetutorwillgainalistofprojectsavailable,butyouarealsoencouragedtocontactotherrelevantorganisationstoidentifyotherpotentiallyfundedprojects.TheapproachyoushouldtakeWhatevertopicyouchoosetostudy,weexpectyoutoadoptanapproachsimilartothefollowing:

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1)Clearlyidentifytheaimsofyourstudiesandstatethemintheintroduction:• WhatamIstudying?• WhyamIstudyingthis?• Howwillthestudybeundertaken?• Towhomwillthefindingsbeuseful?

Stateahypothesisthatyouwishtotestoraresearchquestionthatyouwishtoexplore.2)Reviewtheexistingsituationsoastoputyouraimsintocontext.3)Indicatethemethodsyouintendtouse.4)Collectinformationand/ordataaccordingtoyourstudyplan.5)Analyseyourinformationand/ordataandinterpretitssignificance(usingstatisticaltechniqueswhereappropriate).6)Discussyourresultsandcomparethemwithpreviouswork.7)Reachsomeconclusionsand,ifappropriate,makemanagementrecommendationsbasedonyourstudy.Youmayalsowishtoincludeafinalsectioninyourthesisthatreflectsontheissuesrelatedtoyourproject.Dissertations:WorkingtoaTimetableSubmissionDateYourdissertationmustbesubmittedbefore12:00onthedeadlineday.Dissertationssubmittedafterthisdatewillnotbeacceptedforconsiderationintheacademicyearunlessaccompaniedbyadoctor'snoteindicatingyourinabilitytosubmitontimeandunlessyouhavegivenadvancewarningoflatesubmission,inwritingtoyourprogrammedirectorandthepostgraduateadministrator.Dissertationsthatdonotmeetthisdeadlinewillnotbeconsideredbytheexaminersuntilthefollowingacademicyear.SettingyourselfappropriatetargetsThemosteffectivewaytoensurethatyouareabletosubmityourdissertationontimeistodrawuparealistictimetableofworkandtokeeptothistimetable.Thepreparationofyourdissertationwillprobablyinvolvethefollowingstages:

• Considerationofsuitabletopics• Preparationofadraftproposal

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• Discussionofproposalwithstaff• Revisionandfinalisingproposal• Backgroundreadingandinvestigation• Draftingofinitialchapters(Aims,Methods,LiteratureReview)• Fieldwork• Analysisofdata• Preparationofoutlineofcontentsandstructure• Writingdissertation• Submissionofdrafttosupervisor(s)• Responsetofeedbackondraft• Preparationoffigures• Finalrevisionoftextand‘polishing’ofthesis• Typing/photocopying• Binding• Submission

Itisimpossibletospecifyexacttargetdatesforcompletionofeachofthesestagesthatwouldbeappropriatetoeverytopicandeachindividual,thoughoutlineguidanceisprovided.However,youshouldtrytosetyourselfrealistictargetdatesinrelationtoyourownassessmentofhowlongeachstagewilltakeyoutocomplete.Itisofteneasiesttostartfromthedateofsubmissionandworkbackwardswhensettingyourtargets.Oncetheyareset,sticktoeachtargetdateratherthanadjustingslidingtargetdates.Inpractice,thereisalwaysatemptationtospendlongeronfieldwork,sometimesinthebeliefthatyournextsetofdatawillprovetobethecrucialone.Afailuretobegintheanalysisandwriting-upsufficientlyearlyisthemostcommoncauseoflatesubmission.MoststudentsneedtocompletefieldworkbytheendofJulyattheverylatest,andpreferablyearlier,inordertosubmitontime.LiaisonwithyoursupervisorDonotforgetthatyoursupervisorwillhavemanyotherthingstodoandmaybeawayinAugust.Allowplentyoftimeforconsultationanddiscussionandtrytogiveyoursupervisoraveryclearindicationofthetimetableyouhavesetyourself.Ifpossible,getonwithotherpartsofyourdissertation(e.g.figures,tablesofdata)whilstyoursupervisorisreadingyourdraftthesis.Donotconsultyoursupervisoraboutquitetrivialmattersorsubmitroughdraftsofindividualchapters:yoursupervisorcanonlybeexpectedtocommentonanearcompletedraft.DissertationlengthDonotassumethatyourdissertationwillbemarkeddownforbeingtoobrief.Youwillnotgainextramarksforbeingverboseorfortheweightofthefinaldocument.Youwillbemarkedonthequalityofyourinvestigationandthewayitispresented.Aconcisetextthatdealswithallnecessaryissuesisoftenaqualitytext.Thesesmustnotexceed10000wordswithouttheclearanceofyoursupervisorandjustificationforthiswordlimitextensionmustbestatedtoyoursupervisor.

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Dissertations:UsingStatisticsSomeinformationthatyoumaycollectcannotreadilybesubjectedtostatisticalanalysesandmustbequalitativelyanalysedinasrigorousamanneraspossible.However,providingthatyoucarefullyplanyourexperimentaldesignandmethodsofdatacollection,statisticscanoftenbeusedtosupportyourargument.Indeed,ifacriticalpointisbeingmade,itisessentialtobackthisupwithappropriatestatisticaltestswheneverpossible.Manytextbooksinstatisticsareavailable.Thefollowingtextsarevery"userfriendly"andincludemanyrelevantexamples:DYTHAM,C.1999.Choosingandusingstatistics:Abiologistsguide.Blackwell,Oxford.218ppLEPS,J.&SMILAUER,P.2003MultivariateanalysisofecologicaldatausingCANOCO.CambridgeUniversityPress,Cambridge.SOKAL,R.R.&ROHLF,F.J.(1995)Biometry(3rdEdition).W.H.FreemanandCo.,NewYorkZAR,J.1996.Biostatisticalanalysis.(3rdEdition).PrenticeHall,NJ,USA.718ppManycomputerstatisticspackagesareavailable.Ofthese,MINITABandCANOCOarethemostwidelyused.Theycoveralmosteverystatisticaltestthatyouarelikelytorequire,butremembertousetheappropriatetestratherthanwhatisavailableonthepackageyouareusing.Ifyouhaveaparticularlyintractablestatisticalproblem,youcangainadvicefromyoursupervisororanothermemberofstaff.Moststatisticaldifficultiesarecreatedbypoordesignofdatacollectionmethods.Itisoftendisastroustofirstcollectyourdataandthenaskthequestion"whatstatisticaltestscanIusetoanalysethesedata?"Statisticalanalysisconsiderationsareacrucialaspectofexperimentaldesignsoitiscriticalthatyouseekstatisticaladviceatanearlystageinyourthesisstudy.Wheneveritisappropriateyoushouldfollowthepracticeofusinganullhypothesisbeforecarryingoutatest.Moststatisticaltestsresultinanestimateofthelikelihoodthataparticularresultcouldhavearisenbychance.ThisprobabilityisdenotedbyP.YouareencouragedtoquoteaprecisevalueofP(inwhichcasetheresultisgivenasP=0.014,forinstance).Alternatively,thenormalconventionofindicatingtheprobabilityoftheresulthavingarisenbychanceshouldbeindicatedbytheuseof<(indicatinglessthan)followedbytheappropriatelevel(0.05,0.02,0.01,0.001)takenfromasetofstatisticaltables.Youshouldconformtotheacceptedconventionthatanyresultwithaprobabilitygreaterthan0.05shouldberegardedasnotsignificant.Inmanystatisticalteststheinterpretationofthestatisticcalculatedismeaninglesswithoutthedegreesoffreedom.Thusthesignificancelevelofaparticularvalueof2varieswiththedegreesoffreedomasdoesthesignificancelevelofthecorrelationcoefficient(r).Presentthedegreesoffreedomusingapost-fixtothestatisticalsymbol,e.g.24,r28,t28.

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Youshouldensurethatthetestyoucarryoutisappropriateandthedataareacceptablefortheparticulartest.Donotconfuseparametricandnon-parametrictests.Whenusingpercentagedataremembertocorrectitbyfirstapplyinganarcsintransformationandyoumustnotcarryoutnon-parametricanalysesonpercentagedata.Whensmallsamplesareinvolved,ensurethatthestatisticiscalculatedcorrectlyforsmallsamples(thisincludesYates'correctionforthecalculationof21).Examplesofthestyleinwhichtopresentresultsare:"...andthedifferenceissignificant(21=6.9,P<0.01)""...thecorrelationbetweenAandBissignificant(r28=0.79,P<0.001)""thedifferencebetweenthesamplesisnotsignificant(t17=1.2,n.s.).""ExaminationofthedatausinganANOVA(analysisofvariance)givesF12,23=29.1(P<0.001)."Dissertations:OutlineTimetableforproductionofDissertationThefollowingscheduleisforguidanceonly.Youshouldmakeyourownadjustmentsaccordingtoyourpersonalestimationofhowlongeachstageofyourprojectwilltake.However,youarestronglyadvisedtocompleteeachstageonadatenolaterthanthatsuggestedinthisschedule.Year

• NovembertoJanuaryExploreideasforprojectwithvariousstaffandfindasupervisor

• LateMarchGetdissertationproposalstoyourprogrammedirector• ApriltolateMayWriteinitialsections,designdatagatheringandpreparefor

fieldwork/labwork• MaytolateJulyfieldwork/labwork• EndJulyCompletedataanalyses• LateJuly-mid-AugustWritetextofdissertationandsubmitdrafttosupervisor

(mid-August)• EndAugustEditandworkonsharpeningpresentation.Makethreecopies

andbindtwoincorrectcovers• Dissertationsubmissiondeadline(youcansubmitearlier!)

Remember,thatifdeadlinesstartslidingbackwardsthelatterandmostimportantstageswillendupbeingrushed,andthiswillaffectthequalityofthethesis:prepareascheduleandtryyourbesttosticktoit!