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high-performance computing clusters is needed and knowledge of relevant programming languages (Python, Perl, R) is considered an advantage. A in-depth understanding of biochemistry, genomics experiments
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machine learning. Strong technical background, including substantial experience with programming in Python and relevant ML/statistics libraries (e.g. PyTorch, Darts, Hugging Face Transformers, Pyro, PyMC
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data • Solid knowledge of R, python and/or similar programming languages • Experience with teaching scientific methods • Experience with interdisciplinary science • Interaction with nature
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relevance to the project and with relevance to STS and/or related research in Innovation Studies. Applicants to the postdoctoral fellowship must hold a PhD within STS, Innovation Studies or related fields
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, statistical modelling, programming in R, Matlab, or Python. Excellent skills in written and oral English. Personal suitability and motivation for the position. The doctoral dissertation must be submitted
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recording and analysis, dataset preparation, time-series analysis, statistical modelling, programming in R, Matlab, or Python. Excellent skills in written and oral English. Personal suitability and motivation
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science and biodiversity informatics, in particular handling of scientific collection data • Solid knowledge of R, python and/or similar programming languages • Experience with teaching scientific
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research visits with external collaborators. The position is part of the ERC Starting Grant “Actively learning experimental designs in terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo
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terrestrial climate science (ACTIVATE)”: https://www.mn.uio.no/geo/english/research/projects/activate/index.html The researcher will be part of a growing team of researchers, postdocs and PhD students working
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Care without Harm and the Norwegian Bioart Arena. The Postdoc will also contribute to other project-related tasks and activities. For more information and how to apply: https://www.jobbnorge.no/en