257 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" Postdoctoral positions in Sweden
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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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data using multivariate statistics and machine-learning–assisted approaches, in close interaction with data science collaborators Active collaboration across disciplines spanning spectroscopy, soft
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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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, 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
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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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Biosciences, which offers an international, collaborative, and open-minded research environment. Please visit the lab’s webpage for more information: https://erdemlab.github.io . The Erdem research group is
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Trollhättan The application deadline is 2026-03-01 If you want to learn more about the Swedish Academia please visit: https://sverigesungaakademi.se/en/publications/a-beginners-guide-to-swedish-academia/ We do
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The Department of forest genetics and plant physiology is part of Umeå Plant Science Centre (UPSC, https://www.upsc.se ) which is a centre of excellence for experimental plant research and forest
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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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teaching and learning. The work duties include: The post-doctoral fellow will investigate how stellar and geomagnetic information is sensed and processed by the Australian Bogong moth Agrotis infusa, a model