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calculations; Experience with developing, training, and optimizing neural networks or other machine learning models. For this position we are targeting a salary corresponding to Level 4 Spine Point 28 - 30
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the Drosophila wing as a model tissue, they are also branching out into other tissues in the fly, as well as ex vivo cell/organoid models. The position offers the opportunity to shape a new project in a relatively
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analytical skills in modelling time trends and prevalence data biostatistics for clinical trials and cohort studies experience working with large, multi-wave datasets (e.g., ABS, AIHW, HILDA) reputation at a
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5 Nov 2025 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions Master Positions Country Portugal
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for large samples at ESRF ID16A using multislice tomography approaches. You will lead the development of and work with parallelized computer models to simulate how coherent waves travel through materials with
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associates, and PhD students. Most staff are employed on/funded through external research grants especially from the National Institute for Health and Care Research (NIHR). Other members of IDRIS are based in
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 2 months ago
Stage Researcher (R1) Positions PhD Positions Country Portugal Application Deadline 15 Oct 2025 - 00:00 (Europe/Lisbon) Type of Contract Other Type of Contract Extra Information Research fellowship Job
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digital monitoring solution that enhances energy efficiency and sustainability in manufacturing systems. Using advanced sensing and data analytics, it will generate actionable insights to optimise energy
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students work to create knowledge for a better world. You can find more information about working at NTNU and the application process here . ... (Video unable to load from YouTube. Accept cookie and refresh
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The position is funded by the Open Philanthropy grant “Verifiably Robust Conformal Probes”. The project’s goal is to develop methods for latent probing (aka activation monitoring) of large language models (LLMs