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/or R Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn) Excellent problem-solving, organizational, and communication skills Demonstrated ability to work both
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offer 1-2 specialist positions aimed at increasing the support for SDU’s researchers in developing and winning European collaborative R&I-projects. We hope to hire one junior research supporter on a two
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background in individual- /agent-based modelling Experience with modelling of animal energetics Strong R and Netlogo skills Good understanding of movement & population ecology Experience in publishing
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relevant field. In-depth knowledge and experience with advanced data processing and statistical analysis in R; knowledge and experience in spatial modelling, machine learning, or computational methods
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statistical analyses (e.g. R, Python) Fieldwork experience in ecological or environmental sampling Scientific publishing and project coordination Who we are The Department of Ecoscience is engaged in research
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sample preparation Desirable Qualifications Prior experience with negative ion mode MS is an advantage Interest in computational proteomics workflows Programming or scripting skills (e.g., Python, R
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experience with R, MATLAB or others will also be considered an advantage). Strong communication skills with experience in scientific writing and presenting research to diverse audiences. Able to lead in
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. Proficiency in programming languages such as Python, MATLAB, or R, and familiarity with data analysis libraries (e.g., NumPy, SciPy, Pandas). Demonstrated ability to work collaboratively in a team setting and
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Stata; Knowledge of R, Matlab, Python, and/or Fortran; Experience working with micro data, ideally administrative or matched employer–employee data; Documented research track record at international level
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Willingness to engage in application-oriented R&D, by closely interacting with partners Contact information For further information, please contact Professor Christian Schlette via email (chsch@mmmi.sdu.dk