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around 200 dedicated staff, including 65 PhD students . We are a joint department between Chalmers University of Technology and the University of Gothenburg, combining the best of two academic worlds in
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, Micro-C/Hi-C, BS-Seq/EM-Seq), massively parallel enhancer assays (ATAC-STARR-seq), and comparative/bayesian/deep-learning analyses, with functional validation in spruce via CRISPR-Cas9 and nanoparticle
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systematic research to solve them, if necessary, by learning/adopting new techniques/theories thoroughly understand and conduct good research practices according to the desired time table. be creative and
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results in international peer‑reviewed journals communicate findings to academic and non‑academic audiences Qualifications To be eligible for the position, the applicant must: Hold a PhD awarded ideally no
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qualifications and experience: - A PhD (or equivalent) in neuroscience, biomedical sciences, bioengineering, or a closely related field, obtained no more than a few years before the start date (according to KI
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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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Communication at the Department of Communication and Learning in Science, and a member of our graduate school Communication and Learning in STEM. The division’s research is situated at the intersection
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learning–based protein design, for the successful design of 2D lattices. These methods will then be applied to generate designs targeted for experimental evaluation. Work duties The main duties involved in a
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for near-real-time monitoring of crop growth and early yield prediction, combining remote sensing, machine learning, and crop modeling to support sustainable agriculture. Within the project, we will estimate