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

Helmholtz-Zentrum Dresden-Rossendorf
Dresden, Sachsen (DE)
TVöD Bund
Closing date
Jul 8, 2022

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Life Sciences, Ecology, Physical Sciences, Statistics, Other Physics
Position Type
Full Time
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Organization Type
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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.

Your tasks:

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

Your profile:

  • 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

Our 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

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

For any questions, do not hesitate to ask:
Dr. Justin Calabrese Tel.: +49 3581 37523 71,
Dr. Weronika Schlechte-Welnicz Tel.: +49 3581 37523 72

Place of work:

Working hours:
39 h/week

8 July 2022

Online application
English / German


The HZDR is committed to equal opportunity employment and we strongly encourage applications from qualified female candidates. We also carefully consider all applications from job candidates with severe disabilities.

Bautzner Landstraße 400
01328 Dresden

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.

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