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Praha 120 00, Czechia [map ] Subject Areas: Statistics, data analysis, information theory, machine learning, deep learning, and data science Appl Deadline: 2026/04/16 04:59 AM UnitedKingdomTime (posted
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YOUNG RESEARCHER IN THE FIELD OF EARLY DETECTION OF THE HEALTH STATUS OF PLANTS USING REMOTE SENSING
and features for the pre-symptomatic detection of changes in the physiological status of plants, developing, training, validating, and comparing predictive machine learning and deep learning models
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(R1) Recognised Researcher (R2) Positions PhD Positions Application Deadline 1 Jun 2026 - 12:00 (Europe/Copenhagen) Country Denmark Type of Contract Permanent Job Status Full-time Offer Starting Date 1
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Classification Title: Post Doctoral Associate Job Description: The Department of Epidemiology (http://epidemiology.phhp.ufl.edu/) is strategically situated within the College of Public Health and
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engineering? Then this professor position might be for you. We are looking for a new professor to lead research in probabilistic machine learning, with a focus on areas such as deep generative models, Bayesian
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‑on experience with common machine learning / deep learning frameworks (eg. PyTorch or JAX) applied to biological or structural data. Solid Python programming skills, with experience building maintainable and
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 26 days ago
programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Area of research: PHD Thesis Job description:PhD Position in Machine Learning for Single-Cell Genomics (f
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distributed wireless systems" which is conducted in collaboration between Linköping University (LiU) and Lund University (LU). Read more here: https://elliit.se/project/machine-learning-for-sensing-in
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, engineering, physics, biophysics, applied mathematics, computational biology or a related quantitative field Strong background in deep learning for image analysis / computer vision, ideally on microscopy time
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novel machine learning models—including Physics-Informed Neural Networks (PINNs), variational autoencoders, and geometric deep learning—to fuse multimodal data from diverse experimental probes like Bragg