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focus on Computer Vision, pattern recognition, and visual generative modeling. CVI2 offers the opportunity to contribute to a diverse portfolio of projects, including collaborations with industrial
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and participate in the dissemination of the results through visualizations, publications and presentations. Key Skills, Experience and Qualifications Education: PhD in Bioinformatics, Computational
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effects for drug discovery. The successful candidate will play a leading role in developing gene perturbation models that combine foundation models (FMs) and graph neural networks (GNNs) to accelerate
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outcomes, and multi-OMICS profiles, the project will generate predictive models to guide safer and more effective, individualized steroid use. As such, the candidate will be responsible for data
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BRIDGES project GenePPS, which investigates how machine learning can enable prediction of gene perturbation effects for drug discovery. The successful candidate will play a leading role in developing gene
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control, documentation, automation) Soft skills Ability to work effectively in interdisciplinary teams spanning computational and experimental research Strong analytical and problem-solving skills, with
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The Medical Team of the faculty is in a constant development. Our research initiative, in collaboration with clinical partners, is thriving as we explore the effects of fasting and caloric
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vivo cancer models. The candidate will be expected to: Determine the effects of the identified VFs using various in vitro and in vivo assays and investigate the underlying mechanisms Contribute