305 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" research jobs in Sweden
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. Demonstrated experience in computational methods, particularly in deep learning and computer vision. Understanding or willingness to learn advanced statistical modeling is a plus Assessment criteria and other
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University and the HT Faculties is right for you here, and learn more about Working in Lund , Moving to Lund and Living in Lund . Qualifications The assessment will primarily be based on your research merits
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Description of the workplace The Division of Secure and Networked Systems at the Department of Electrical and Information Technology conducts broad research in cryptography, computer security
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the future of research? Find more reasons why Lund University and the HT Faculties is right for you here, and learn more about Working in Lund , Moving to Lund and Living in Lund . Qualifications
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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce
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. Our research is focused on cell biology, spatial proteiomics and machine learning for bioimage analysis. The aim is to understand how human proteins are distributed in time and space, how this affects
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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for machine learning, e.g. PyTorch or TensorFlow. Strong ability in spoken and written Swedish. Assessment of the applicants will primarily be based on scientific merits and potential as researchers. Special
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completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service
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factor that strongly modifies turbulence, pressure drop, and heat transfer. Unlike conventional machined roughness, AM roughness is characterized by randomness, porosity, and powder adhesion, producing