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/Statistics, Medical/Health Informatics. Strong computational and programming skills with abilities to develop cutting-edge large-scale machine/deep learning algorithms using high-performance computing (HPC
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secondments. The project envisages the following secondments: a three-months secondment to learn novel algorithms form improving fecal MP samples' taxonomic and functional characterization (Prof. Bart Mesuere
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of Vienna . We are looking for a Senior Scientist to join the 'Dynamics of Stellar Systems' research group led by Prof. Glenn van de Ven. Our ideal candidate has a solid background in computational
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Australian National University | Canberra, Australian Capital Territory | Australia | about 8 hours ago
to climate, health, and environmental challenges. Strong candidates will have experience in ML algorithms, human-centered ML, or NLP. Supported by an ARC Future Fellowship and CSIRO-NSF project. Computational
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of Stellar Systems' research group led by Prof. Glenn van de Ven. Our ideal candidate has a solid background in computational astrophysics, strong track record in software development, and keen interest in
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period of 6 months (starting November 1, 2025, with the possibility of extension up to a total duration of 12 months) Is the job funded through the EU Research Framework Programme? Not funded by a EU
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21 Aug 2025 Job Information Organisation/Company TU Dresden Research Field Computer science » Other Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1) Established Researcher
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and
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Algorithms. The candidate is expected to conduct research in computer science focusing on the combinatorial aspects of quantum experiments and quantum algorithms for computational geometry problems. Prior
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VR/AR, quantum tech, life-sciences, computing and biomedical imaging. The project will work on cutting-edge optical technologies alongside collaborators Prof Melissa Mather, Prof Dmitri Veprintsev, and