93 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Switzerland
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. Conduct statistical analyses of the acquired datasets. Contribute to the publication and presentation of research findings. Assist in the supervision of Ph.D. students. Profile Prerequisites: PhD. degree in
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progress Profile Required PhD in Computer Science with the focus on AI Proficiency in python programming Strong expertise in machine learning and deep learning frameworks (especially PyTorch) Demonstrated
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types. Profile A PhD in Computational Materials Physics or a related area is required. Experience with electronic structure calculations, including writing computer code, is essential. Familiarity with
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of circularly polarized / chiral phonons in quantum paraelectric materials. Job description The postdoctoral researcher will develop machine-learned force fields trained on density functional theory (DFT) outputs
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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoc position for the development of metal
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excel in collaborative environments and can bring expertise in any of the areas above, we strongly encourage you to apply. Qualifications PhD in Physical Chemistry, Chemical Engineering, Material Science
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Researcher (R2) Country Switzerland Application Deadline 4 Jun 2025 - 21:59 (UTC) Type of Contract Temporary Job Status Full-time Hours Per Week 41 Is the job funded through the EU Research Framework Programme
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Zurich and is supervised by Prof. Livia Schubiger. The candidate will work with the IRDS group on projects that leverage NLP, causal inference, and machine learning to explore norms related to gender-based
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are required to have: A completed PhD degree. Experience in machine-learning methods. Some skill in at least one of these topics: Large data sets analysis Statistics and uncertainty analysis (probabilistic
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of spintronic devices. Job description You will be responsible for developing novel spintronic devices for computing applications. The characterisation will be carried out using lab-based characterisation methods