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, longitudinal modelling, machine learning and multivariate approaches. Proficiency in programming (e.g., MATLAB, Python, or R), handling large datasets, and working with complex analysis 2 pipelines is an
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analysis, machine learning, mathematics of data scienceMathematical modeling and manifold learning of high-dimensional data geometry, with theoretical foundations and applications in evolutionary biology and
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publications in established machine learning, computer vision, artificial intelligence, and robotics venues. Depending on the contribution and maturity of the work, relevant conferences include NeurIPS, CVPR
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individuals participating in studies investigating the cardiovascular consequences of preterm birth. By combining fluid dynamics, machine learning, and advanced imaging analysis, the project seeks to develop
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/DPhil in robotics, computer science, machine learning, informatics, AI, or a closely related field. You will have an excellent academic track record in topics relevant to locomotion and manipulation; path
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high-resolution mass spectrometry, in vitro pharmacological characterisation of new psychoactive substances, as well as metabolomics and machine learning. As a PhD student, you devote most of your time
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. Qualifications PhD in epidemiology or related field. Demonstrated expertise in use of epidemiology or machine learning theory in study of chronic disease conditions. Strong record of peer-reviewed publications
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be preferred. Requirements: PhD degree in Learning Sciences, Educational Technology, Human-Computer Interaction (HCI), Information Technology, AI, or a relevant field Demonstrated experience and
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. About You You will have a PhD in computer science, engineering, mathematics, or similar, strong programming skills, and experience with a contemporary machine-learning framework such as PyTorch. You will
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discovery through public and Novartis-internal datasets. We are looking for candidates with A PhD in machine learning, computer science, computational biology, or a closely related field (completed or near