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of the materials will allow you to explore high-temperature thermodynamics and elasticity. The theoretical challenge is to develop a machine learned interatomic potential based approach in exploring the vibrational
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. Knowledge of AI and machine learning techniques Experience in the AI application to structural bioinformatics or related areas. Familiarity with the AlphaFold platform and its applications in protein
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another way. If you can say yes to some of the below points it is highly beneficial: Proficiency in programming languages, preferably Python. Knowledge of AI and machine learning techniques Experience in
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have significantly more experience, e.g. already have a Ph.D. Previous experience with DFT ab-initio calculation of materials coupled with experience with machine learning algorithms is particularly
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university’s Norrköping Campus. MIT is an international leader in interdisciplinary, applied research with expertise in visualization, design, computer graphics, and learning science. The research nexus
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documentation of the above stated requirements and merits is expected. A PhD in Computational Physics, Scientific Computing, Mathematics or similar with a strong programming and machine learning background
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your application! We are looking for up to four (4) PhD students in Computer Science within CUGS Research School formally based at the Department of Computer and Information Science Your work
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properties under decompression or are even directly synthesizable at ambient conditions. We will use density functional theory based calculations, machine learning based techniques and work in close
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northern Europe. Our research covers a broad spectrum of fields, from core to applied computer sciences. Its vast scope also benefits our undergraduate and graduate programmes, and we now teach courses in
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Machine learning methods High performance computing Multivariate analysis As a person, you are self-motivated and structured. You easily adapt to changing circumstances and find it easy to cooperate with