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programming (e.g., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication
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Laboratory seeks a postdoctoral appointee to join a multidisciplinary team developing complex systems models, including agent-based models, and new algorithms and tools for machine learning and optimization
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genome-based influenza and/or SARS-CoV-2 risk assessment algorithms, designing broadly protective influenza and SARS-CoV-2 vaccines using Machine Learning and Artificial Intelligence, modeling the impacts
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in cilia. Transport within cilia, the cell’s signalling and sensory antennae, is central to human biology. It enables these cell-surface organelles to assemble and dynamically change their proteome in
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Dutch and English. Affinity or experience with innovation projects involving partners from practice. Willingness or experience in programming heuristics and algorithms. Motivation to produce academically
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: Exploring how non-classical states of light can enhance modern microscopic imaging techniques. Designing setting up and executing the experiments Developing relevant algorithms for experimental data post
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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. The most recent methodological research of the group includes algorithms for cell type deconvolution, high-resolution purification, and integration of single cell multi-omics data. This postdoctoral fellow
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., Python, MATLAB). Preferred Qualifications: Experience in resilience analysis for multi-agent systems. Familiarity with communication-constrained algorithm design. Prior work on communication-efficient and
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activities related to externally funded projects. This may include developing and evaluating algorithms, collecting data during experimental testing, and performing other types of research. 3. Report