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Engineering, Computer Engineering, Mechatronics Engineering, Physics, Electrical Engineering, Chemical Engineering, Mechanical Engineering or other related subjects. Experience working on experimental
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. For more information see https://www. umu.se/en/research/groups/nausica-privacy-aware-transparent-decisions-group-/ The postdoctoral position is funded by WASP Wallenberg AI, Autonomous Systems and Software
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specialization in freshwater ecology, limnology or similar fields. We seek a candidate with experience in leading scientific publication process, and the ideal candidate must demonstrate ability to produce high
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degree. This eligibility requirement must be met no later than the time the employment decision is made Strong written and verbal communication skills in English Documented experience from modern LC-MS
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. Documented research experience in modern deep learning (e.g. generative models, Bayesian deep learning or large pre-trained models) and excellent programming skills in Python and a modern deep learning
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regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures (https
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at international conferences, contribute to collaborations, and participate in the supervision of junior researchers. You may also contribute to the development of new experimental platforms and research directions
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topics within applied economics. Applicants should have experience with experimental methods and/or empirical analysis of observational data with an emphasis on causal inference. Experience with methods
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structured manner, as well as excellent collaboration skills, be able to independently plan and conduct experimental studies and effectively manage and resolve unforeseen challenges, have experience with cell
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experience from modern LC-MS method development and analysis You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research and education. The following experience