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graduated at Master’s level in machine learning, statistics, computer science, fluid mechanics, or a related area that is considered relevant for the research topic of the project, or have completed courses
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, computer science, fluid mechanics, or a related area that is considered relevant for the research topic of the project, or have completed courses with a minimum of 240 credits, at least 60 of which must be in
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doctoral candidate will investigate new strategies to control the electronic properties of organic semiconductors through innovative doping mechanisms. The work will combine tailored molecular and materials
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assignments Your tasks will be to carry out research using advanced theoretical and computational methods within quantum mechanics and statistical physics with the aim to study novel materials synthesized