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Position: Professorship for methods of Machine learning in geophysics
Institution: Universität Hamburg
Location: Hamburg, Germany
Duties: The successful candidate is expected to conduct basic research in the field of machine learning or, more generally, data-driven analyses in geophysics. We are especially interested in the application of these methods to problems in solid Earth geophysics, especially the propagation of seismic waves or subsurface imaging using the methods of applied geophysics. In addition to the development of machine learning strategies for (automated) data analysis, the candidate should draw conclusions about fundamental physical processes via reverse engineering. Synergies with the research being conducted in other research groups at the Institute of Geophysics is highly desirable
Requirements: Applicants are expected to have international research experience in the field of machine learning in geophysics as well as initial experience in acquiring external funding and carrying out externally funded projects. Projects and publications as well as a broad interest in geophysics issues should attest to the applicant’s research activities
   
Text: UniversitätHamburgisdedicatedtosustainability,equalopportunity,andfamily-friendlypol-icies.Wealsoprizeculturaldiversity,communication,andinteractionamongpeoplefromdif-ferentbackgroundsandwithdifferentlifestyles.AsaUniversityforsustainability,weputhumanresourcesdevelopmentandespeciallythede-velopmentandadvancementofourearlycareerresearchersattheforeofourstrategicendeav-ors.Bystrengtheningthetenure-trackprofessorship,UniversitätHamburghasintroducedanewcareeropportunityforearlycareerresearchers.Duetothesuccessofthetenure-trackprogramrunbytheMinistryforEducationandResearchandtostrengthentheresearcharea/researchareasClimate,EarthandEnvironment,Universi-tätHamburginvitesapplicationsforthefollowingtenure-trackprofessorship:TheFacultyofMathematics,InformaticsandNaturalSciencesinvitesapplicationsforaTENURE-TRACKProfessorship(W1TenuretrackleadingtoaW2)formethodsofMachinelearn-ingingeophysicscommencingassoonaspossible,Ref.no.JP296.Responsibilities:Thesuccessfulcandidateisexpectedtoconductbasicresearchinthefieldofmachinelearningor,moregenerally,data-drivenanalysesingeophysics.Weareespeciallyinterestedintheappli-cationofthesemethodstoproblemsinsolidEarthgeophysics,especiallythepropagationofseismicwavesorsubsurfaceimagingusingthemethodsofappliedgeophysics.Inadditiontothedevelopmentofmachinelearningstrategiesfor(automated)dataanalysis,thecandidateshoulddrawconclusionsaboutfundamentalphysicalprocessesviareverseengineering.SynergieswiththeresearchbeingconductedinotherresearchgroupsattheInstituteofGeophysicsishighlydesirable.ParticipationintheUniversity’scoreresearchareaClimate,EarthandEnvironmentisalsoare-quirementoftheposition.Integratingclimate-relatedresearchtopics(e.g.,carboncaptureandstorage(CCS),perma-frost)amongotherthingsisdesirable.ThecandidatecancooperatewiththeCenterforEarthSystemResearchandSustainability(CEN)andincurrentprojectsintheClus-terofExcellenceClimate,ClimaticChange,andSociety(CLICCS)aswellasinitiatehisorherownprojects. Inbothresearchandteaching,thecandidateisexpectedtocooperatewithothernationalandinternationalinstitutionsandtoinitiatethecreationofnew,externallyfundedresearchpro-jects.Wefurtherexpectthecandidatetoleadascientificresearchgroupandtakeanactivepartinacademicself-governance.ThesuccessfulcandidateisexpectedtoteachcoursesingeophysicsintheBachelorofScienceandMasterofScienceinGeophysicsaswellastoparticipateintheteachingandsupervisionofdoctoralcandidates.Section12subsection7sentence2oftheHamburghighereducationact(HamburgischesHochschulgesetz,HmbHG)applies.Requirements:Academic qualifications and additional requirements as specified in Section18HmbHG.Additionalcriteria:Applicantsareexpectedtohaveinternationalresearchexperienceinthefieldofmachinelearn-ingingeophysicsaswellasinitialexperienceinacquiringexternalfundingandcarryingoutex-ternallyfundedprojects.Projectsandpublicationsaswellasabroadinterestingeophysicsis-suesshouldattesttotheapplicant’sresearchactivities.TheUniversityplacesparticularempha-sisonthequalityofteachingandthereforerequeststhatapplicantsprovidedetailsoftheirteachingexperienceandobjectives.The post holderis expected to acquire the language skills necessary to teach in German (Level C1 of the Common European Framework of Reference for Languages) within two years of com-mencing employment providing he or she does not have the requisite skills when starting.Atenure-trackevaluationwillbeconductedduringthesecondphaseofthejuniorprofessorshipinordertodeterminewhetherrequirementsforappointmenttoaW2professorshiphavebeenmet.Section15HmbHGapplies.Iftheevaluationispositive,thecandidatewillbeofferedaten-uredW2professorship.Theregulationsprohibitinginternalappointments(Hausberufungsver-bot)alsoapplytothisjuniorprofessorship.In accordance with Section14subsection 3sentence3HmbHG, UniversitätHamburg seeks to in-crease the proportion of women in teaching and research and encourages female academics to apply.Qualified disabled candidates or applicants with equivalent status receive preference in the ap-plication process.Hearingsarescheduledtotakeplaceon10October2019and11October2019.For further information, please contact Prof. Dr. Celine Hadziioannou at +49 40 42838-2980 or celine.hadziioannou@uni-hamburg.deand Prof. Dr. Matthias Hort at +49 40 42838-3969 or matthias.hort@uni-hamburg.de.The application deadline is 15August 2019. Please submit your application with your CV, list of publications, teaching experience, external funding record, copies of certification and docu-ments, three representative publications, teaching and research plans, and the reference num-ber JP 296, preferably by email in a single PDF file, to: Bewerbungen@verw.uni-hamburg.deor UniversitätHamburgiscertified.auditfamiliengerechtehochschuleper post to:An den Präsidenten der UniversitätHamburgStellenausschreibungenMittelweg 17720148 Hamburg
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