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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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image/signal processing, particularly in computer vision.Strong programming skills and experience with at least one deep learning framework e.g. TensorFlow or PyTorchFamiliarity with machine learning and
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Description We are seeking a motivated new PhD candidate who wants to join an exciting collaborative research program within the VIB-Center for Inflammation Research between the Guilliams, Saelens
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Saelens team. Research Project In this research project you will develop probabilistic deep-learning models that automatically extract biological and statistical knowledge from in vivo perturbational omics
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meaningful feedback to patients, clinicians and policymakers The PhD will work at the interface of machine learning, deep learning, geospatial AI, causal modelling, and digital health systems. Your Role You
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About us VIB.AI, the VIB Center for AI & Computational Biology, is a research center dedicated to integrating machine learning with deep biological insight to understand complex biological systems
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contribution of the PhD will be the derivation of multilayered approaches for motion planning and control based on the XS-Graphs, where both model-based and learning-based solutions are foreseen. This includes
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optimization techniques. You have experience with modern Deep Learning Frameworks (PyTorch, Tensorflow, Jax) and proven ability of CUDA and Python programming. Knowledge of, or prior experience with, optimizing
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, and computational models. This PhD position is centered on addressing these challenges through innovative computational methods, combining optical system design, signal processing, machine learning, and
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venuesStrong programming skillsSolid mathematical foundation, including linear algebra, probability, statistics, and optimizationBroad and in-depth experience with machine learning algorithms and deep learning