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visualization of high-dimensional omics data from the field of bioeconomics, and in the modeling, simulation, and engineering of biomolecular systems, including enzymes. Apply your data science skills to real
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transitions in and out of campus housing, accurate data reporting, and collaborative partnerships across departments. As part of our integrated residential education model, you’ll work closely with professional
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have extensive knowledge on processes governing cross-shore transport and can use experimental data to develop predictive models. Experiences within numerical modelling of coastal processes is considered
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at unprecedented resolution. The core innovation of your work will be integrating this data to train deep learning models that predict chromatin accessibility and gene expression patterns. These models will
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appropriate balance of synergy and complementarity with materials science and engineering research already underway. Alignment with Materials Ageing, Performance, and Lifetime Prediction and a willingness to
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are considered the largest source of uncertainty in climate predictions because it is complicated to accurately model the small-scale process (microphysics) inside clouds occurring in a range from meters to
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clinical study to develop prediction models for periodontal disease progression (funded by the National Institute of Dental and Craniofacial Research). Primary responsibilities of the Study Coordinator will
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) brief approach (models, data/testbeds), (iv) evaluation plan, and (v) alignment with IDLab research on flexible and deterministic networking at the University of Antwerp (https://www.uantwerpen.be/en
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workflows that integrate modern AI and machine learning concepts (e.g., surrogate models, adaptive sampling strategies) into the drug discovery pipeline to increase throughput and predictive accuracy
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developing models that predict the effects of variants. We tackle this challenge via two main directions: (1) developing efficient pangenomic data structures and evolutionary models, and (2) designing deep