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networks. The research will employ mathematical modelling and computer simulation to identify synaptic plasticity rules which enable effective learning in large and deep networks and is consistent with
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successful courses or projects) Be proficient in programming (preferably in Python ot Matlab). Ideally familiar with machine/deep learning, signal processing, dynamical system or mathematical modelling To find
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machine learning for next-generation wireless networks, (ii) Foundations of semantic communications and age of information, (iii) Stochastic geometry and spatial modeling of large-scale wireless systems
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the communication and presentation of scientific data. The intern will gain new skills in machine learning pipelines, model training and data management. Job Duties Attends weekly lab meetings. Works with trainees
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atmospheric chemistry, air quality, and model development. Basic Qualifications: Ph.D. in atmospheric science and substantial experience in modeling of atmospheric composition. Additional Qualifications
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network models on computing clusters Knowledge, Skills and Abilities: Demonstrated fluency in Python, and willingness to keep up with new machine learning libraries (pytorch, lightning, …) Knowledge
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
degree of independence and commitment Experience with machine learning and high-performance computing is advantageous, but not necessary Our Offer: We work on the very latest issues that impact our society
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an exceptional opportunity to conduct cutting-edge research at the intersection of machine learning, healthcare, and computational modelling, contributing to real-world clinical impact. What is offered
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in machine learning and/or computer security and Experience working with LLMs or agent-based systems. Informal enquiries may be addressed to adel.bibi@eng.ox.ac.uk For more information about working at
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mathematical foundation of machine learning models. You will be responsible for developing scientific machine learning methodologies enabling new approaches for solving machine learning problems including