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2,900 work in administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Startdate
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 10 days ago
the Medical University of Vienna, the Technical University of Vienna and University of Vienna, the AITHYRA and CeMM PhD programs for both life scientists and computational scientists/machine learning experts
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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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at the interface of machine learning, statistics, and live-cell biology. The position is co-supervised by Prof. Olivier Pertz (Cell Biology) and Prof. David Ginsbourger (Statistics), and the student will be equally
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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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. Machine learning will assist in artifact correction, segmentation, and material classification. By combining experimental imaging, simulation, and data-driven interpretation, this approach will deliver high
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PI & HOSTING GROUP The direct responsible persons for this post are Dr. Joost van de Weijer and Bogdan Raducanu, members of the Learning and Machine Perception (LAMP) team at the CVC. For more
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administration and organisation. We are looking for a/an University assistant predoctoral/PhD Candidate Optical Quantum Computing and Machine Learning 51 Faculty of Physics Job vacancy starting: 01.02.2026 (MM-DD
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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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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