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Offer 391 out of 630 from 09/06/22, 10:26

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Helm­holtz-Zen­trum Dres­den-Ros­sen­dorf e.V.

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 sys­tem sci­ence, sys­tems bio­logy and mater­i­als research.

As part of the insti­tute, the Depart­ment of Earth Sys­tem Sci­ence invites applic­a­tions for postdoc­toral pos­i­tion focused on devel­op­ing stat­ist­ical meth­ods to estim­ate encounter rates from animal track­ing data.

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

PostDoc (f/m/d) Quan­ti­fy­ing encounter rates from animal track­ing data

English

Working field:

The suc­cess­ful can­did­ate (f/m/d) will be part of an inter­na­tion­ally renowned team that focuses on stat­ist­ical meth­ods devel­op­ment for animal move­ment data. This work will build on and extend recent efforts to develop the­ory (Mar­tinez-Gar­cia et al. 2020) and stat­ist­ical meth­ods (Noonan et al. 2021) related to encounter pro­cesses. The researcher (f/m/d) will then use the res­ult­ing estim­at­ors to per­form global-scale com­par­at­ive ana­lyses in a large, multi-spe­cies track­ing data­set.

  • Develop stat­ist­ical meth­ods to estim­ate a range of encounter-related met­rics from animal relo­ca­tion data
  • Per­form cross-spe­cies com­par­at­ive ana­lyses of encounter pro­cesses on a large, multis­pe­cies animal track­ing data­base
  • Work closely with col­lab­or­at­ors whose col­lect­ive expert­ise spans field eco­logy, the the­ory of encounter pro­cesses, and stat­ist­ical meth­ods and soft­ware devel­op­ment
  • Pub­lish res­ults in aca­demic, peer-reviewed journ­als
  • Present res­ults at sci­entific meet­ings

Lit­er­at­ure cited:

Mar­tinez-Gar­cia, R., Flem­ing, C. H., Sep­pelt, R., Fagan, W. F., & Calabrese, J. M. (2020). How range res­id­ency and long-range per­cep­tion change encounter rates. Journal of The­or­et­ical Bio­logy, 498, 110267.

Noonan, M. J., Mar­tinez-Gar­cia, R., Davis, G. H., Cro­foot, M. C., Kays, R., Hirsch, B. T., ... & Fagan, W.F., Flem­ing C.F., and Calabrese, J. M. (2021). Estim­at­ing encounter loc­a­tion dis­tri­bu­tions from animal track­ing data. Meth­ods in Eco­logy and Evol­u­tion, 12(7), 1158-1173.

Requirements:

  • PhD degree in Quant­it­at­ive Eco­logy, Phys­ics, Stat­ist­ics, Data sci­ence, Machine learn­ing, or a related field
  • Exper­i­ence in model-based stat­ist­ical ana­lysis and stat­ist­ical meth­ods devel­op­ment
  • Advanced pro­gram­ming skills in R
  • 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
  • Prior exper­i­ence work­ing with animal track­ing data is advant­age­ous but not required

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
  • An employer sub­sidy for the VVO job ticket

How to apply:

Kindly sub­mit your com­pleted applic­a­tion (includ­ing cover let­ter, CV, dip­lo­mas/tran­scripts, etc.) only via our Online-applic­a­tion-sys­tem: https://www.hzdr.de/db/Cms?pNid=490&pLang=en&pOid=66198