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Field
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candidate with skills and experience in some of the following areas: Quantitative approaches such as longitudinal data analysis, analysis of large datasets and/or data science Experience of working with
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to the ongoing research in Prof. Marcotti’s laboratory by designing, developing and performing experiments, data analysis and disseminating the findings by writing articles and by presenting findings
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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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special emphasis on a relaxed and cooperative working environment. Social interactions help facilitate active scientific exchange and foster a good atmosphere, and therefore play a big role in our team
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class of medicines. However, progress in this area has been limited by the absence of high-quality, large-scale protein¿peptide interaction datasets critical for rational, AI-driven peptide design. To
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currents form the deepest canyons, longest channels and largest sediment accumulations on our planet. They also break seafloor telecommunication cable networks that form the backbone of global data transfer
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tools are need during the development of new imaging and sensing systems. With the rapid deployment of data-driven methods, repliable uncertainty quantification remains a big challenge that requires
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childhood into adulthood. The role involves working with large-scale longitudinal datasets to explore gene–environment interplay and developmental risk pathways. The successful candidate will join a vibrant
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complements LCAB’s research programmes. High competence in the analysis of large ecological and other data sets and time series. Ability to write up research for publication in high profile journals, along with
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real