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evaluations Solid programming skills in at least one relevant language (e.g., Python, C++) Interest in interdisciplinary work involving engineering, sustainability, and real-world infrastructure Strong written
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to network modelling, network theory and/or network meta-analyses. Fluency in programming as needed for network analyses (e.g., R/python) Strong analytical, organisational, and record-keeping skills
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. Your competencies We thus imagine that you: have a strong background in digital signal processing and machine learning; have substantial experience with scientific computing in Python/C++/ROS; know
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Computer Science and Mathematics. A background in algorithm design and implementation combined with solid programming skills (e.g., Java, C, C++, Python), is highly valued. Candidates are expected to contribute
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Neural Networks Deep Learning and Uncertainty Quantification Python and ML frameworks (TensorFlow, PyTorch, JAX) Reproducible and open-science practices Experience with geospatial, environmental
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background in thermodynamics and phase behavior of complex mixtures Excellent programming skills (e.g., Python, C++, Fortran, or similar) Experience with COSMO-based methods, including parameterization, model
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Qualifications Ph.D. in Bioinformatics, Computational Biology, Systems Biology, or a related field Proven experience in the analysis of single-cell or spatial omics datasets Strong programming skills in Python and
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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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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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) multiscale fluid simulation methods (CFD, LBM, PNM, MD) scientific programming (Python, C++, git) microfluidic experimentation Why Join SDU Sønderborg? The SDU Energy Systems Group at CIM is a dynamic