194 phd-studenship-in-computer-vision-and-machine-learning Postdoctoral positions in Sweden
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, TensorFlow, JAX). Demonstrated ability to work in interdisciplinary teams bridging machine learning, neuroscience, and chemistry. Excellent communicative skills and Collaborative abilities Motivation and
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), research is carried out in computer vision, robotics and machine learning. We are now looking for two postdocs in robotics and machine learning and computer vision. The successful candidates is expected
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candidate with an interest in the application of machine learning to optics, touching upon aspects of computational electromagnetism and inverse design. Information about the project and division Structured
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the application of machine learning to optics, touching upon aspects of computational electromagnetism and inverse design. Information about the project and division Structured optical materials, such as
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through 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 Job description This advertisement is
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research project (e.g. PhD in physical chemistry, chemical physics, computational chemistry or relevant) and needs to be passionate about research. Experience in usage Gaussian, ADF, Dalton, ORCA etc
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into consideration. The applicant must have, or be about to receive, a doctoral degree in a subject relevant to the research project (e.g. PhD in physical chemistry, chemical physics, computational chemistry or
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qualified and motivated postdoctoral researcher. The group studies the behavioral, neural, and computational principles behind human learning and decision-making in social environments. Our interdisciplinary
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areas. Qualifications To be eligible for a postdoc position, you must have a PhD in Computer Science, Automation, Electronics, Mechatronics, Industrial IT, or another relevant subject area. The PhD should
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Demonstrated experience with LS-DYNA or comparable commercial FEA software Proficiency in Python programming for scientific computing and machine learning applications Experience with machine learning methods