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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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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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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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absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment
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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
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may be considered if there are special grounds, such as sick leave, parental leave, clinical service, service as a union representative, military service or similar, or service/assignment of relevance
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, parental leave, appointments of trust in trade union organizations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant
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in radiotherapy with the goal of enabling fully adaptive radiotherapy. The work is based on deep learning, where models are trained on generated or clinical data. The project is carried out in
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of the following areas: state models, time series analysis, computational statistics, unsupervised machine learning, optimisation, model predictive control. Experience in financial mathematics. Having high integrity