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, phylogenetics/phylogenomics, omics-data integration, machine learning and visualisation techniques. This project will be performed in collaboration with experts in different fields, and keeping possibilities open
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machine learning approaches show issues in model performance and efficiency and vulnerability towards the application of noise over a large number of distributed models. These issues should be overcome by
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for: PhD Candidate, Reinforcement Learning for Sustainable Energy This position is embedded
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relevant to both the healthcare sector and society at large. We are looking for a PhD student in Biomedical Engineering Sciences in the field of biological systems modeling and deep learning Your work
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Schoonjans (Pediatric Neurology Department UZA) are seeking a highly motivated PhD student to work on clinical data analyses and multi-omics approaches in the rare genetic neurodevelopmental syndrome, STXBP1
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willingness to learn and apply machine learning approaches We offer A versatile and challenging job in a vibrant and world-class research environment operating at an international levelParticipation in a large
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computational and data science capabilities in Swedish life sciences. DDLS is establishing a research school for 260 PhDs in academia and industry. The aim is to educate highly skilled and competent professionals
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We are looking for a doctoral candidate with a strong computational, engineering, data scientific or machine learning background that is keen to work in an interdisciplinary environment and open to
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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for Computer Vision conducts research and education in machine learning for computer vision at the undergraduate, advanced, and PhD levels. CVL has been identified as an outstanding Swedish research environment