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Field
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23 Jan 2026 Job Information Organisation/Company DIFFER Research Field Chemistry » Computational chemistry Chemistry » Physical chemistry Engineering » Chemical engineering Researcher Profile First
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modelling predictions. Experience or a strong interest in scientific programming and machine-learning-assisted data analysis for materials modelling is an advantage. PhD Position 2 – Coarse-Grained and
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical devices Develop hardware-aware machine learning models incorporating electronic and optical
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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composites for enhanced durability, performing microstructural analysis and mechanical testing. Topology Optimization & AI Integration: Use AI and machine learning to guide structural and topology optimization
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Engineering Telecommunications Engineering Data Science / Artificial Intelligence Computer Engineering Applied Computing Computer Science Or a closely related discipline Equipped with advanced scientific and
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. You are driven by scientific curiosity, enjoy working with complex multi-physics models, and are eager to advance probabilistic methods, machine learning tools, and simulation techniques. If you thrive
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Physics , Living Systems , Machine Learning , many-body quantum geometry; altermagnetism; cavity quantum science; quantum non-equilibrium processes; Casimir physics , Material Science , Materials Science