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computational costs by orders of magnitude and enabling breakthroughs in drug design and materials science. The position bridges machine learning and molecular science, with opportunities for collaboration
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for radio-based positioning and sensing (localization, tracking, ISAC), combining physical modeling, probabilistic inference, and modern machine learning in collaboration with international partners. About us
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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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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce using UPSC transformation and somatic embryogenesis pipelines; evaluating drought
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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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the beginning and there is still much to be learned! You will lead a project that centers on how tactile end organs assemble, function, and recover after injury. You will be using non-standard animal models
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mathematics to work with Axel Ringh on a project funded by the Swedish Research Council (VR). The project is centered around inverse optimal control/inverse reinforcement learning, both for continuous-time and
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, appointments of trust in trade union organisations, military service or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. The doctoral