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following: Quantum chemistry (preferably of excited states) Multiscale simulations/environmental modelling Excited state dynamics Data Science/Machine learning in chemistry/Cheminformatics Molecular dynamics
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member of either our Electrical Power or Fluid Mechanics research nodes. The Electrical Power Research Node comprises a group of eight academics with seven research associates and 20 PhD students. We have
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matching post based at Teesside University); (3) nature and natural heritage (the focus of a matching post based at Newcastle University); (4) active evaluation for learning (e.g. research conducted by team
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the ecosystem. Any decline in bee populations could pose a threat to global agriculture. In this context, the EU-funded RoboRoyale project is developing and combining micro-robotic, biological and machine
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KTP Associate in Machine Learning ( Job Number: 25000811) Department of Computer Science Grade 7: - £39,105 - £43,878 per annum Fixed Term - Full Time Contract Duration: 30 months Contracted Hours
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interfaces, rheology, fluid dynamics across scales, lubrication and wetting, biophysics as well as machine learning or metamaterials. For experimentalists, we are particularly interested in applicants aligned
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Engineering, potentially including Power Electronics, Machines and Drives, Network Optimisation and Reliability, with the ability to teach our students to an exceptional standard and to fully engage in
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operation · Application of artificial intelligence or machine learning in energy or engineering systems 5. Strong programming and modelling skills using relevant tools such as Python, MATLAB
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centralised machine rooms to host our high performance computers. The Department is committed to research-led and small group teaching. The Complete University Guide ranks Durham's Physics Department in fourth