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Field
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outcomes Synthetic data generation (virtual patients) Statistical model checking to ensure statistical correctness of the results Machine learning–based classification and regression methods The candidate
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. Preferred Qualifications Ph.D. degree in a biomedical science-related field Previous experience working with rodent models and rodent behavioral tests/analyses. A minimum of 3 years of laboratory experience
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or above). For more details please check the Graduate Schools Admission Requirements: https://www.tudelft.nl/onderwijs/opleidingen/phd/admission . TU Delft (Delft University of Technology) Delft University
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will generate synthetic data from personal data to mitigate scarcity in rare diseases. This will facilitate data availability for further development of predictive models, thereby enhancing the quality
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of pseudorange correction models. Enforcing such constraints offers substantial potential benefits, including faster convergence, improved generalisation, and reduced overfitting. At the same time, these benefits
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, electrical engineering, communications engineering or similar - Solid computer science and analytical skills, including modelling and verification, programming language theory or quantitative model checking
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predictive checking, model comparison) • Computational modelling with Python and Dynesty, JAX, NumPyro, and PyTorch • Use of asteroseismic and spectroscopic survey data (e.g. PLATO, Gaia, APOGEE, TESS) • High
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
results. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will model the mechanical properties and plastic deformation of materials with diverse
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models remain limited to the world of standard dynamic range (SDR). This project seeks to bridge that divide, unifying methods and technologies designed for both SDR and HDR content-spanning still images
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, 3, 12, 13): DC2: Infection biomarker discovery in chronic wound models DC3: Infection biomarker monitoring in environmental samples DC12: Optimizing bioreceptor function in interaction with graphene