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Helm­holtz-Zen­trum Dres­den-Ros­sen­dorf e.V. - PostDoc (f/m/d) Machine learn­ing for animal move­ment ana­lysis

Through cut­ting-edge research in the fields of ENERGY, HEALTH and MAT­TER, Helm­holtz-Zen­trum Dresden-Rossen­dorf (HZDR) solves some of the press­ing soci­etal and indus­trial chal­lenges of our time. Join our 1.400 employ­ees from more than 50 nations at one of our six research sites and help us mov­ing research to the next level!

The Cen­ter for Advanced Sys­tems Under­stand­ing (CASUS) is a Ger­man-Pol­ish research cen­ter for data-intens­ive digital sys­tems research. CASUS was foun­ded in 2019 in Görl­itz and con­ducts digital inter­dis­cip­lin­ary sys­tems research in vari­ous fields such as earth sys­tems research, sys­tems bio­logy and mater­i­als research.

As part of the Insti­tute, the Depart­ment of Earth Sys­tem Sci­ence invites applic­a­tions as PostDoc (f/m/d) Machine learn­ing for animal move­ment ana­lysis.

The pos­i­tion will be avail­able from 1 Octo­ber 2022. The employ­ment con­tract is lim­ited to two years.

Job Back­ground and Scope:

The suc­cess­ful can­did­ate (f/m/d) will be part of an inter­na­tion­ally renowned team that focuses on devel­op­ing ana­lyt­ical method and soft­ware for animal move­ment data. The can­did­ate’s work will broaden the focus of the group’s efforts to encom­pass the applic­a­tion of ML tech­niques to prob­lems includ­ing, but not lim­ited to, the clas­si­fic­a­tion of indi­vidu­als as range res­id­ent (or not), the iden­ti­fic­a­tion of beha­vi­oral states in track­ing time series, and the integ­ra­tion of mul­tiple data streams (e.g., GPS loc­a­tion data and accel­er­o­meter data). This research will lever­age a large, multi-spe­cies track­ing data­set for both train­ing and cross-val­id­at­ing the ML algorithms.

PostDoc (f/m/d) Machine learn­ing for animal move­ment ana­lysis


Working field:

  • Design, imple­ment and com­pare a range of machine learn­ing (ML) tech­niques for solv­ing chal­len­ging prob­lems in move­ment eco­logy
  • Develop open-source soft­ware imple­ment­ing the suc­cess­ful ML approaches for a broad user audi­ence
  • Identify ana­lysis prob­lems in move­ment eco­logy that are par­tic­u­larly amen­able to ML approaches
  • Pub­lish res­ults in peer-reviewed, aca­demic journ­als
  • Present res­ults at sci­entific meet­ings


  • PhD degree in Machine Learn­ing, Stat­ist­ics, Data Sci­ence, Quant­it­at­ive Eco­logy, Phys­ics or a related field
  • Exper­i­ence in devel­op­ing and imple­ment­ing mod­ern machine learn­ing meth­ods
  • Advanced pro­gram­ming and pack­age devel­op­ment skills in R
  • Prior exper­i­ence work­ing with animal track­ing data is advant­age­ous but not required
  • Excel­lent com­mu­nic­a­tion skills in Eng­lish in a pro­fes­sional con­text (present­a­tion of research res­ults at sci­entific meet­ings, col­lo­quial dis­cus­sions, manuscript writ­ing)
  • Evid­ence of the abil­ity to pub­lish res­ults in top peer-reviewed journ­als

What we offer:

  • A vibrant research com­munity in an open, diverse and inter­na­tional work envir­on­ment
  • Sci­entific excel­lence and extens­ive pro­fes­sional net­work­ing oppor­tun­it­ies
  • The employ­ment con­tract is lim­ited to two years
  • Salary and social bene­fits in accord­ance with the col­lect­ive agree­ment for the pub­lic sec­tor (TVöD-Bund) includ­ing 30 days of paid hol­i­day leave, com­pany pen­sion scheme (VBL)
  • We sup­port a good work-life bal­ance with the pos­sib­il­ity of part-time employ­ment and flex­ible work­ing hours
  • Numer­ous com­pany health man­age­ment offer­ings

How to apply:

Kindly sub­mit your com­pleted applic­a­tion (includ­ing cover let­ter, CV, dip­lo­mas/tran­scripts, etc.) only via our Online-applic­a­tion-sys­tem: