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to target leading venues such as NeurIPS, ICML, ICLR, AISTATS, AAAI, ECAI, and TMLR. The postdoc will join the PSAI research group and will be supervised by Associate Professor Andrés R. Masegosa
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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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the project “cross-disciplinary R&D of molten salt reactors” we address key challenges in MSR technology development: the characterization of complex fuel salt-material interactions and the development
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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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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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: Extensive experience in programming using Python, R, or other languages Research experience in remote sensing of cover crop, crop type classification, and crop aboveground biomass quantification Insight
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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 programs
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. Experience with omics approaches. Working with human pathogenic bacteria. Molecular studies of AMR mechanisms. Data-analysis skills (R-Studio or similar). Knowledge of or interest in natural product chemistry
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languages such as Python or R. Experience with machine learning, systems biology, or network modeling approaches. Previous expertise in human cardiometabolic or complex diseases, with domain expertise in but