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for additional teaching. The Department of Religious Studies has five full-time faculty and a history of innovative teaching and the promotion of independent learning. The Department's website is http
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articles based on the results obtained. The goal of this work is to explore and prototype different integration strategies, evaluate their effectiveness in selected machine learning or neuroevolution tasks
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your machine learning expertise to cutting-edge automated optimisation challenges? We are seeking a Research Fellow in Digital Chemistry and Engineering to combine self-optimising flow reactor technology
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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simulations, machine-learned force fields, and artificial intelligence (AI). The successful candidate will lead the development of a computational platform that unifies first-principles methods, classical
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, computer simulations and machine-learning analyses. The University of Nottingham offers a wide range of employee benefits. More information can be found at: https://www.nottingham.ac.uk/hr/your-benefits/a-z
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independently and as part of a team Experience with machine learning and AI applications in engineering is advantageous We regret to inform that only shortlisted candidates will be notified. Hiring Institution
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep