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Field
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complex dynamics. In parallel, collective decision-making mechanisms (e.g., opinion dynamics) will be leveraged at the high level to coordinate the desired behaviours of multi-agent systems in response
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GPU-capable, parallelized simulation frameworks. Work closely with experts in HPC and power systems to enhance scalability and computational performance. Disseminate your findings through scientific
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We are looking for a highly motivated PhD student to join the Nucleic Acid Immunity Lab at the VIB-UGent Center for Inflammation Research. Lab website: https://www.irc.ugent.be/groups/maelfait-lab
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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tested by isothermal titration calorimetry (ITC) or microscale thermophoresis (MST) in collaboration with the lab of Prof. Andy Lovering. In parallel, minibinder/effector pairs will be co-expressed using
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with an in depth characterization of the underlying mechanism(s) and genetic consequences. In parallel, we also aim to identify key genetic regulators of the meiotic reductional division in banana as a basis
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high-resolution, quantitative time-lapse soil property measurements using high-performance, parallel computing. Together with our existing rich dataset, we will inform a soil-plant digital twin, enabling
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activation processes catalyzed by transition metals. In parallel, we work on the design and synthesis of bifunctional compounds for selective catalytic reactions. In particular, we are interested in
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techniques); giving mathematical proofs of their correctness and efficiency; building state-of-the-art implementations of these new techniques (e.g., by leveraging data-parallel functional array programming
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single-cell proteomics approaches on patient samples to gain additional resolution on cell-state diversity within tumours. In parallel, you will collaborate closely with a postdoctoral researcher to