155 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions in Finland
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of educational work Practical experience in teaching and efforts to improve teaching, digital teaching skills, and giving feedback, possible participation in continuous learning provision, and international
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. The university lecturer must have the readiness to acquire research funding. The appointee must have an interest to work in a multilingual and multicultural working environment and in crossdisciplinary groups and
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to promoting diversity, equality, and non-discrimination in all its activities. Thus, we promote equal opportunities to learn, acquire knowledge, participate, and make a difference. As an equal-opportunity
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be filled for a fixed-term period of 3 months, commencing on 1 June 2026 or as mutually agreed. Trial period of 1 month applies. 1. Aerosol physics https://www.tuni.fi/en/about-us/aerosol-physics
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machine learning techniques, and GPU programming. The simulation results will be compared to observational data obtained using facilities worldwide including ESO and NOT. Who we are looking for A successful
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teach German language and culture to students who have no previous knowledge of the subject. The position is part of the national SARAVE project of Finnish universities and located at the University
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cooperation in a multidisciplinary environment Pedagogical studies, merits and experience Merits in supervising Bachelor’s, Master’s and doctoral students Proficiency in Finnish or strong motivation to learn
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) to study talk and interaction in multinational crisis management training. The studied situations involve military and civilian personnel who are trained to participate in international peace-keeping and
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resolution by integrating plasmonic nanopores with a high-speed Raman detection system, an automated control system, computer simulations, and advanced Raman-based bioinformatics. The RamanProSeq consortium
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(linking phenotypes, imaging, cytometry, or other readouts to transcriptomics) Statistics / machine learning for biological inference (model validation, differential state testing, embeddings/classifiers