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Postdoc in Computational paleobiology

CH 1700 Fribourg
24.02. | Position with re­spon­si­bil­i­ties | 100%

Postdoc in Computational paleobiology


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  • \r The positions are funded by the Swiss National Science Foundation. We offer a stimulating, friendly and interdisciplinary work environment, with excellent working conditions and a very wide international network of collaborators. Funding will also be available for travel and research visits in research institutions abroad. The postdoc will also have the possibility to co-supervise a PhD project in the lab.\r
  • \r The Department of Biology of the University of Fribourg (Switzerland) gathers very dynamic and diverse researchers with a strong commitment toward innovation and excellence in science. It offers a stimulating and international environment, with an open-minded atmosphere ideal to foster synergies.\r
  • \r The Postdoc position is fully funded for 2 years with a possibility for an extension. In addition, the postdoc will have the possibility to apply to prestigious and generous fellowships from the SNF to start an independent career after completion of their postdoctoral fellowship.\r
\r \r For more information:\r

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  • \r Silvestro group:\r
  • \r Research groups in Ecology and Evolution:\r
  • \r Research groups in Bioinformatics:\r
  • \r Department of Biology:\r


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  • \r We are looking for a postdoctoral researcher with a strong background in computer science or computational biology/geology to develop new methods to analyze large paleo-biological data sets.\r
  • \r The postdoc will have access to large fossil datasets and time series from past and ongoing drilling projects and will use them to make inferences about evolutionary processes.\r
  • \r Their research will focus on implementing new models to date the fossil record based on biostratigraphy using Bayesian and/or machine learning algorithms.\r
  • \r The details of the projects will be developed together with the postdoc based on their interests and skills.\r


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  • \r PhD in Computer Science, Biology, or Earth Sciences\r
  • \r Excellent ability to communicate and write in English\r
  • \r Demonstrated ability to program in Python or R\r
  • \r Experience with Bayesian methods and/or machine learning algorithms\r
  • \r Strong publication record\r
\r \r Additional desirable skills:\r

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  • \r Experience in other programming languages such as C/C++\r
  • \r Knowledge in the fields of macro-evolutionary biology, geology, paleontology, biostratigraphy\r

Sprachliche Anforderungen.

andere: English



Daniele Silvestro
T: +41 26 300 88 57


Short cover letter (max 2 pages) explaining background, motivation, research interests\r
A complete CV (including publication list and links to online repositories or software developed by the applicant)\r
Contact information for 2-3 referees who may be contacted during the evaluation of the applicant\r
Applications will be evaluated by a committee and shortlisted candidates will be invited for an interview (by Skype or in person).

Position with re­spon­si­bil­i­ties, 100%


Université de Fribourg

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