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engineering Engineering » Other Researcher Profile First Stage Researcher (R1) Application Deadline 30 Apr 2026 - 20:59 (UTC) Country Finland Type of Contract Temporary Job Status Full-time Is the job funded
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activities. We also have access to real quantum hardware, including VTT’s Q50 and Helmi machines and Aalto’s Q20, all located right downstairs from our offices. In addition, access to other leading commercial
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Doctoral Researchers (PhD students) to work on deep learning methodologies for machine and robot perception. These positions are funded by the Horizon Europe project OPERA (Open Perception, Learning, and
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), Computational Biology (stochastic and analytical models of gene expression), Signal Processing (machine learning, image and signal processing), Biophysics, Microbiology and Single-cell Biology (flow cytometry
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more than five years ago at the time of accepting the position. In this context, the 5-year limit refers to a net period of time, which does not include maternity leaves, parental leaves, military service
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on developing novel Machine Learning methods for financial markets. The positions will offer excellent opportunities to work in a team of professionals responsible for developing cutting-edge technologies in
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processing, machine learning, statistics or related fields. Demonstrated expertise in ML/AI, with prior experience of applications in the healthcare domain, particularly in cancer research considered a strong
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workflows that integrate modern AI and machine learning concepts (e.g., surrogate models, adaptive sampling strategies) into the drug discovery pipeline to increase throughput and predictive accuracy
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across all areas in Computer Science, including Algorithms and theory Bioinformatics and digital health Computing systems and networks Cybersecurity Human-computer interaction Machine learning and
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inequalities and Sobolev-type spaces (with Hytönen and/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic