113 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" research jobs in Finland
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- UNIVERSITY OF HELSINKI
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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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net period of time, which does not include parental leaves, military service etc.) good skills in spoken and written English motivation for research work in aerosol physics or chemistry. Please note
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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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communication Demonstrated track record in scientific writing and publishing We also appreciate the following know-how and experience in: Experience from machine and deep learning data analysis Experience from
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, interests, and strengths, offering a flexible and rewarding research environment. Our expectations of the applicant A solid background in remote sensing Strong computer and software skills, including
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of this unusual Brain-Computer Interface. More information: (7) BRAINET: Overview | LinkedIn The doctoral candidate at Tampere University will develop tools and methods to assess the effects of the non-invasive
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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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to align with your strengths and preferences. Our expectations of the applicant We are seeking candidates with: • A strong background in remote sensing • Excellent computer and software skills (e.g
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, military service etc.) Excellent/good skills in spoken and written English. English is used as the language of instruction and supervision in this position. Expectations A formal background in bioinformatics
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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