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germplasm characterization, including calculation of sequence based genomic prediction and genomic selection values. To learn more about the USDA ARS NPGS and Plant Genetic Resources, visit our webpages
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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4 Aug 2026 Job Information Organisation/Company Technological University Dublin Department Human Resources Research Field Technology » Computer technology Researcher Profile Recognised Researcher
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Background in machine learning or deep learning methods, including Graph Neural Network (GNN) Experience with Large Language Models (LLMs) applied to biological data collection, extraction, and standardization
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initiation latency, movement speed, gait characteristics, postural control, motor variability, and other behavioural descriptors. ESSENTIAL REQUIREMENT PhD in machine learning, artificial intelligence
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. The project will involve drone optimizations, computer vision, closed-loop control, multi-modal sensor fusion, machine learning, and transfer learning methods. The candidate will also work in collaboration with
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in tropical regions; analyze links between macrofauna and soil carbon; build/validate scoring algorithms using machine learning/cumulative functions. Outputs – Lead scientific, technical, and policy
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 1 day ago
. Candidates with expertise in related areas, such as lattice field theory algorithms, machine-learning methods for lattice field theory, hadron spectroscopy, or hadron-structure phenomenology, are encouraged
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Curious about opportunities for learning, creating, discovering, and innovating, and are encouraged to learn from failure. Show Your Fire by joining our team and exhibiting your passion and pride in your
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an advantage: plasma surface functionalization; electrode/electrolyte interfaces; battery degradation modelling; microstructure-resolved modelling; tomography or image-based electrode modelling; machine learning