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. Experience in experimental cell biology, programming, biophysics, image analysis, genomics or data analysis is considered meritorious. The project will be conducted in a multidisciplinary research
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): Analysis of omics-data or other large-scale biomedical data types Machine-learning and statistical modelling Mechanistic models of biological systems Python, R or equivalent programming environment
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processing and analyzing large ecological datasets Documented experience with terrestrial laser scanning (TLS) data acquisition and processing Experience with scientific programming or scripting and
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, hydraulics/hydrology, thermodynamics (e.g. heat transfer processes) - experience of sensor-based monitoring, field sampling, machine learning, programming as well as working with large environmental
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with X-ray imaging techniques, e.g. µCT, nanoCT, TXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability to work both independently and as part of a team
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in Python programming for geospatial data processing, modeling, and mining. Publications in high-quality international peer-reviewed journals within a relevant field, especially experience in
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. Proven experience with X-ray imaging/diffraction techniques, e.g. XRD-CT, 3D-XRD, µ/nanoCT, STXM or similar. Experience in computer programming for data analysis, e.g. Python. Demonstrated ability to
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group develops theory, methods and software for data-driven science, with a current focus on uncertainty quantification in large pre-trained models (vision-language models), generative models (flow
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programming environments, especially R or Python; the applicant’s ideas concerning how the OCCPOL data could be developed and used; and motivation to participate actively in a collaborative research project and