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Materials Science for Sustainability (WISE) and Wallenberg AI, Autonomous Systems and Software Program (WASP), a WASP-WISE NEST. This interdisciplinary setting provides a unique opportunity to work at the
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training programme complementing scientific skills with personal and entrepreneurial skills, including communication to various audiences, career development, intellectual property and startup-funding
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treatment. It is advantageous if you have previously worked with massively parallel sequencing (NGS), both in the laboratory and/or with bioinformatics, for example Single Cell RNAseq. It is also advantageous
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First Stage Researcher (R1) Country Sweden Application Deadline 29 Sep 2025 - 22:00 (UTC) Type of Contract To be defined Job Status Full-time Is the job funded through the EU Research Framework Programme
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- 12:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a
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novel machine learning method development. However, you will be part of a larger cross-disciplinary research initiative involving both computer and material scientists, providing excellent opportunities
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Meritorious is if you have: experience with the statistics program R experience with various immunological methods such as flow cytometry and proliferation previous experience of working in a research group
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energy, energy storage, electronics, medicine, sustainable manufacturing, etc. The main focus for the advertised position is novel machine learning method development. However, you will be part of a larger
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is experiences in interprofessional education and learning. Meritorious is experience in student-centered learning, such as problem-based learning (PBL), which is the pedagogical method used
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undergraduate and advanced levels, primarily in our engineering program in Construction Engineering and our master's program in Digitalized Construction. Course orientations where you may be involved include