12 big-data-machine-learning-phd PhD positions at University of Copenhagen in Denmark
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/ . Interviews with selected candidates are expected to be held in week 43-44. Questions For specific information about the PhD fellowship, please contact the principal supervisor. General information about PhD
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used will be Density Functional Theory, statistics, machine-learning and dynamics. Collaboration with members of other research groups at UCPH and abroad is required. Who are we looking for? We
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points Participating in active research environments including a stay at another research team Obtain experience with teaching or other types of dissemination related to your PhD project Teach and
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. For information of eligibility of completed programmes, see General assessments for specific countries and Assessment database . Terms of employment Employment as PhD fellow is full time and for maximum 3 years
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across two leading institutions. For more information about the double degree framework, please visit the (SDC) website. (https://sdc.university/research/for-phd-supervisors/ ). Who are we looking for? We
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skills. For further information about the guidelines for PhD studies at UCPH, please refer to: https://phd.ku.dk/english/. For further information about the structure of the PhD programme, please refer to
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involves the use of quantum chemistry, machine learning, and genetic algorithms to search for new homogeneous chemical catalysts. Who are we looking for? We are looking for candidates within the field
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PhD plan (1-2 pages) Curriculum vitae including information about your education, experience, language skills and other skills relevant for the position Original diplomas for Bachelor of Science or
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the Pharmaceutical Sciences bridging Health Sciences and Life Sciences. Information about the Department can be found at https://drug.ku.dk/ Job description Your key tasks as a PhD student at the Faculty of Health and
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interdisciplinary environment, which offers fantastic scientific and social interactions with a large group of talented researchers. Further information on the Niels Bohr Institute is found at https://nbi.ku.dk