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Python for scientific computing – experience with data analysis and basic signal processing – foundations in machine learning and interest in developing advanced AI models – familiarity with Linux
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Experience and practical knowledge of programming languages and tools (e.g. Python, Java, etc.) Knowledge in Software Engineering, AI, machine learning is an advantage Experience with software observability
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to optimise built-environment thermodynamics and occupant comfort by creating predictive AI tools for spatiotemporal heat transfer. Machine learning algorithms will identify energy inefficiencies and propose
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., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by
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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 Startdate: 01.02.2026 | Working hours
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, network analysis, or machine learning are a plus Good organisational skills and ability to work both independently and collaboratively Effective communication skills and an interest in contributing to a
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of everyday life. This project aims to change that by developing AI-driven methods to assess wellbeing through video-based sentiment analyses. As a PhD student, you will develop and refine machine learning
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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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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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/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