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Max-Del­brück Cen­ter (MDC)/ Ein­stein Cen­ter for Digi­tal Future (ECDF) - data sci­ence

HEIBRiDS is a joint gradu­ate pro­gram in Data Sci­ence of the Helm­holtz Asso­ci­ation and the uni­ver­si­ties asso­cia­ted with the Ein­stein Cen­ter for Digi­tal Future (ECDF), namely Humoldt Uni­ver­si­tät, Char­ité Uni­versitätsmed­izin, Freie Uni­ver­si­tät, and Tech­ni­sche Uni­ver­si­tät Ber­lin. Estab­lished in 2018, HEIBRiDS is an inter­dis­cip­lin­ary pro­gram that trains young sci­ent­ists in Data Sci­ence applic­a­tions within a broad range of nat­ural sci­ence domains, span­ning from Earth & Envir­on­ment, Astro­nomy, Space & Plan­et­ary Research to Geosciences, Mater­i­als & Energy and Molecu­lar Medi­cine. It is our goal to edu­cate a new gen­er­a­tion of research­ers, who are skilled data sci­ent­ists that under­stand the demands and the chal­lenges of the dis­cip­lines in which data sci­ence has become indis­pens­able.

Inter­dis­cip­lin­ary Data Sci­ence Research in Ber­lin – 10 fully-fun­ded PhD fel­low­ships

Helm­holtz Ein­stein Inter­na­tional Ber­lin Research School in Data Sci­ence

Work­ing field:

The Helm­holtz Ein­stein Inter­na­tional Ber­lin Research School in Data Sci­ence (HEIBRiDS) invites applic­a­tions for PhD fel­low­ships in a col­lab­or­at­ive research envir­on­ment across dis­cip­lin­ary bor­ders. HEIBRiDS pro­jects com­bine Data Sci­ence with applic­a­tions in Molecu­lar Medi­cine, Mater­i­als & Energy, Earth & Envir­on­ment, Geosciences and Space & Plan­et­ary Research and top­ics belong to one or more of the fol­low­ing areas:

  • Machine Learn­ing & Deep Learn­ing
  • Data Man­age­ment
  • High-through­put Data Ana­lyt­ics
  • Math­em­at­ical Mod­el­ling
  • Ima­ging

Research will be con­duc­ted at one of the part­ner Helm­holtz Cen­ters in the Ber­lin region:
  • Max Del­brück Cen­ter for Molecu­lar Medi­cine (MDC)
  • Deutsches Elektronen-Syn­chro­tron (DESY)
  • Helm­holtz-Zen­trum Ber­lin (HZB)
  • Ger­man Research Centre for Geosciences (GFZ)
  • Alfred-Wegener-Insti­tut (AWI)
  • Ger­man Aerospace Cen­ter (DLR)

or the par­ti­cip­at­ing Ein­stein Cen­ter Digital Future (ECDF) part­ner uni­versit­ies:
  • Tech­nis­che Uni­versität Ber­lin (TU)
  • Char­ité - Uni­versitätsmed­izin Ber­lin
  • Freie Uni­versität Ber­lin (FU)
  • Hum­boldt-Uni­versität zu Ber­lin (HU)

If you enjoy work­ing in an inter­dis­cip­lin­ary envir­on­ment, pro­du­cing cut­ting-edge research, come and join our inter­na­tional com­munity in Ber­lin, Ger­many!

What we of­fer:

  • Cut­ting-edge research in data sci­ence under close super­vi­sion of a team of two ment­ors
  • Three-year fully-fun­ded fel­low­ships (E13 TVöD or TV-L), with a pos­sib­il­ity of one-year con­tract exten­sion
  • Integ­rated train­ing cur­riculum of sci­entific and pro­fes­sional skills courses taught in Eng­lish
  • Fin­an­cial sup­port for con­fer­ences and col­lab­or­a­tions

How to ap­ply:

To apply, a mas­ter's degree in quant­it­at­ive sci­ences (Com­puter Sci­ence, Phys­ics, Stat­ist­ics or Math­em­at­ics) or related applied field (Bio- or Geoin­form­at­ics etc.), awar­ded by July 2020, is required.

Apply by Feb­ru­ary 7, 2020, via the online HEIBRiDS applic­a­tion portal. Please sub­mit your CV, aca­demic record, con­tacts of two ref­er­ees, and motiv­a­tion let­ter refer­ring to one or two of the avail­able doc­toral pro­jects. Detailed descrip­tion of the doc­toral pro­jects will be avail­able upon regis­tra­tion to the applic­a­tion portal.

Suc­cess­ful can­did­ates will start their PhD between July and Octo­ber 2020.

For more inform­a­tion, visit our webpage: https://www.heibrids.berlin/admission/open-phd-positions/

We adhere to prin­ciples of respons­ible research, good sci­entific prac­tice, open­ness and trans­par­ency, and are com­mit­ted to set­ting a good example as a sci­entific envir­on­ment where sci­ent­ists can flour­ish and grow, inde­pend­ently of their national or eth­nic back­ground, func­tional vari­ation, sex/gender iden­tity/align­ment/ori­ent­a­tion, fam­ily con­fig­ur­a­tion, or other such fea­ture of their per­sons or con­texts.

Severely dis­abled per­sons will be given pref­er­en­tial treat­ment in the case of equal qual­i­fic­a­tion.