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, computer science, electrical engineering, or a related field. Strong interest in doctoral research on audio deepfake detection, watermarking, source tracing, and generative AI. Good programming skills
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engineering, or a related field. Strong interest in doctoral research on audio deepfake detection, watermarking, source tracing, and generative AI. Good programming skills, preferably including Python and
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algorithms and data analytics tools, and share your results with experimental collaborators. The position is part of the Research Council of Finland project ELPH-ML ( https://research.fi/en/results
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programming, GPU programming) Astrophysical fluid dynamics and/or magnetohydrodynamics Radiative transfer in astrophysics Machine learning or data analysis for physical sciences Strong programming
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data processing Experience in scientific writing and academic publishing Programming skills and experience with MATLAB, Python, or similar tools Familiarity with machine learning and deep learning
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coursework (examples): Computational physics/scientific computing and numerical methods for PDEs High‑performance computing (parallel distributed programming, GPU programming) Astrophysical fluid dynamics
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independently and in a team, and an interest in working with industry partners Willingness to do hands-on work underground and in the laboratory Basic programming ability in Python, MATLAB, R, or similar
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advantage. Good data-analysis and programming skills (e.g., Python, MATLAB, or similar). A hands-on approach to experiments, patience in troubleshooting, good communication skills, and the ability to
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mass transfer. Experience with microscopy, surface characterization, nanofabrication, or experimental instrument development is an advantage. Good data-analysis and programming skills (e.g., Python