18 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"Iscte-IUL" positions at University of Basel
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Your profile We seek candidates with an outstanding research record in deep learning, in particular in one or several of the following areas: modeling and architecture development, domain adaptation
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-omics datasets Developing and maintaining reproducible, well-documented analysis pipelines Applying and adapting machine learning and AI approaches to biological questions Collaborating closely with
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. • Familiarity with machine learning, dimensionality reduction, clustering, and statistical modeling. • Strong communication skills, interest in interdisciplinary work, and ability to train students and postdocs.
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Health (AICH) group develops AI/ML methods, digital tools, and secure data pipelines to advance pediatric healthcare. We work at the intersection of clinical medicine, machine learning, and data-intensive
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responses approximate human behavior. The project involves a collaboration between behavioral and computer scientists. The ideal candidate has some knowledge in both areas, and the specific behavioral domain
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, computer literacy and motivation to further develop technical skills (e.g., programming), and a strong work ethic.
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, “Embodied Learning”, physical activity and sport in Developmental Disorders, and the cognitive effects of physical activity and sports in school settings. Our research group adopts a methodological approach
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of novel physics-guided AI algorithms for drug design, integrating physics-based modeling with state-of-the-art deep learning methods. The project will focus on creating a next-generation docking framework
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topics. You collaborate on research and pedagogical projects and assist in academic administration to some degree. You will teach two hours per week (during the semester).
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computer scientists, experimentalists and clinicians. You will be involved in cross-disciplinary collaborations and have training opportunities to further develop and grow your scientific interests. Access