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simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical
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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
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flexibility for the PhD researcher to develop their own research ideas, and that plans or topics may evolve based on advancements in academic literature or emerging opportunities. Nonetheless, the primary
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by VIB.AI Scientific Director Stein Aerts, is seeking a talented postdoctoral researcher to develop next-generation sequence-to-function models for glioblastoma (GBM). Glioblastoma is the most
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-driven applications. Given the scientific expertise developed within the MYRRHA project, the Belgian government tasked SCK CEN to conduct research on lead-cooled SMRs (LFR-SMR) with the aim of building a
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observations of the marine environment, enhancing our understanding of the dynamics and functioning of marine and coastal ecosystems. MOC focuses on developing, operating, and optimizing innovative, integrated
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description You will work at the interface of experimental biophysics, mechanobiology, and quantitative biology, developing and applying innovative approaches to characterize mechanical phenotypes across scales
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and therapy. LipidBRIGHT will train 11 scientists in a close cooperation between academia, SMEs and industry partners. Key objectives are to provide: Excellent scientific training on interdisciplinary
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early developmental success. You will establish an integrated workflow that combines cryo-electron tomography (cryo-ET), sub-tomogram averaging and expansion microscopy to map/model key sperm structures
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computational genomics and Alzheimer’s disease to develop and/or apply computational approaches to large scale genomic or transcriptomic datasets for identification of targets for early detection, prevention