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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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preferably with data analysis and machine learning (e.g., Python, AI frameworks). You have strong analytical and problem-solving skills, with the ability to translate complex clinical processes into structured
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work. Availability for a ≥4 month stay abroad. Background in at least one of: AI/machine learning, computational modelling, microscopy, or cell/molecular biology. LanguagesENGLISHLevelGood Additional
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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/10.1021/acs.jpcb.4c01558 ], but they lack accuracy for predictive modelling. Transferable machine learning potentials, like MACE-OFF [https://doi.org/10.1021/jacs.4c07099 ], effectively achieve quantum
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Department/Location: Department of Biochemistry, Central Cambridge PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based
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well as the programmes in statistics, cognitive science and innovative programming. Read more at https://liu.se/ida The position is based at the Division of Statistics and Machine Learning (STIMA). We conduct research
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industrial component given the close collaboration with the quantum computing start-up, Quantum Motion, particularly with Dr. Ciriano-Tejel, machine learning group. Key responsibilities Conduct research
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senior members in the lab, and at the same time to play an active role in shaping and creating inspiring research and working environment. In line with our and Uni Basel values (https://www.unibas.ch/en
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promise and peril of hybrid intelligence—humans and machines working and learning together. Our mission is to establish an internationally leading interdisciplinary hub that advances foundational research