174 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" "UCL" "UCL" "UCL" positions in Finland
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- UNIVERSITY OF HELSINKI
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Helsinki, Vaasa, Porvoo, and Hamina. Helsinki, Pitäjänmäki: motors, generators, drives, robots, CPM energy management systems and paper machine drive solutions, global ABB Ability™ platform development, and
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of materials development. They will teach across the Department’s undergraduate and graduate programmes and majors. Your role and goals You will support students in establishing their independent and critical
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, digital teaching skills, and giving feedback, possible participation in continuous learning provision, and international educational collaboration Production and use of learning materials, including open
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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
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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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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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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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. 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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of solar energy systems, applying machine learning methods, and data analysis. A background can be in materials engineering, physics, electrical engineering, computer science, or another suitable field. In
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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