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tumour response to treatment can then bring this much-needed clarity, and implementing this understanding into computational tools can provide the potential for rapid clinical response to patients
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communication skills are encouraged to apply. A MSc degree (or equivalent) in Mechanical Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic
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achieved consensus. The PRELIFE consortium brings together leading researchers from a wide spectrum of disciplines—including astronomy, biology, chemistry, computer science, earth and planetary sciences
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular
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for this position will have the following qualifications/qualities A PhD degree in either machine learning or computational molecular sciences. Advanced knowledge in molecular machine learning. Advanced knowledge in
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computational skills and to conduct a sophisticated applied research project. Organisation The PhD position is embedded in the research programme EEF of FEB’s Research Institute. The project will be supervised by
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chain management in a short research proposal. Organisation The PhD position is embedded in the research programme Opera of FEB’s Research Institute. The project will be supervised by dr. Chengyong Xiao
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. Organisation The PhD position is integrated into the OPERA research programme of FEB's Research Institute. This PhD project is part of the Care2Change initiative, organized by the consortium "Sustainable
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the Faculty of Science and Engineering, a 4-year PhD position is available to start as soon as possible at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence with the topic
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institution has granted a Master's degree in Engineering, specializing in mechanical engineering, electrical engineering, computer science, mathematics, or a related field, along with a notable academic track