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, or as soon as possible thereafter Project Description We invite applications for a postdoctoral position at the interface of computational proteomics, machine learning, and mass spectrometry. The
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Machine Learning Employer University of Southern Denmark (SDU) Location Odense, Fyn (DK) Salary Competitive Closing date 16 Nov 2026 View more categories View less categories Discipline Chemistry
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programming in Python, R, or similar languages Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to
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machine learning for plant biology Employer Aarhus University (AU) Location Aarhus, Midtjylland (DK) Salary Competitive Closing date 12 Oct 2026 View more categories View less categories Discipline
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Join us at the Department of Electrical and Computer Engineering at Aarhus University for a two-year postdoctoral position focused on physics-driven machine learning for ground-based, airborne, and
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cognitive support and corrective feedback. You will apply advanced algorithms for machine learning, multimodal biosignal processing, and human-state inference, working with shared-control strategies and
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employment. Publication Track Record: At least two first-author research papers at flagship venues of core machine learning research (e.g., NeurIPS, ICML, ICLR, AISTATS). Theoretical Rigor: A deep
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structured, well-documented way that supports benchmarking, reproducibility, and reuse by others. Essential: Strong data analysis and machine learning skills and experience with PyTorch (or equivalent
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Postdoc in first-principles modelling and machine-learned force fields for correlated disorder in...
Chemistry at the Institute of Materials Chemistry, TU Wien. The group develops and applies electronic-structure theory, machine-learning methods and predictive calculations of defects and transport properties
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end, we are looking for candidates interested in developing new machine learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this