265 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" Postdoctoral research jobs in Sweden
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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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ways to transform towards them. Finally, we will synthesize our learning across cases to enhance causal multispecies understanding of biodiversity. The postdoctor will work with the Swedish team but is
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. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com/ad/chalmers-university-of-technology/2026/postdoc
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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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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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-emitting devices and other advanced optoelectronic applications. The positions are based in the Green Nanodots Group (https://www.umu.se/en/research/groups/green-nanodots/ ), Department of Physics, Umeå
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offering a high living standards, access to a sprawling city life as well as the beautiful nature surrounding the city. https://ki.se/en/research/research-areas-centres-and-networks/research-groups/robert
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Umeå Plant Science Centre (UPSC, https://www.upsc.se ) which is a centre of excellence for experimental plant research and forest biotechnology in Northern Sweden. Our mission is to perform excellent and
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regular project meetings and collaborate closely with other members of the research group. Publish scientific articles, both independently and in collaboration with others. Teach up to 20% of your working
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data using multivariate statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft