170 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" PhD positions in Denmark
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in the group of Niels Engholm Henriksen (https://www.kemi.dtu.dk/english/research/physical-chemistry ). You must have a solid foundation and interests in quantum chemistry, applied mathematics
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to analyse and interpret complex data. ability to work independently and take initiative, good hands-on problem-solving skills, and the capacity to acquire new skills. We know that research shows that women
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mentorship. Application deadline: 27h of February 2026 at 23:59 hours local Danish time Please see the full call, including how to apply, on https://fa-eosd-saasfaprod1.fa.ocs.oraclecloud.com/hcmUI
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environments This PhD project investigates the use of digital technologies (environmental sensing, user feedback loops, computer vision, machine learning) and theories of human perception and behavioral nudging
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. Benefits and salary The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Early-Stage Researchers (http://ec.europa.eu/research/mariecurieactions
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. An individual career development plan containing research and transferable courses, international research visits, mentoring and career activities, is also a central element. Please visit https://www.interact
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% of all employees are internationals. In total, it has more than 600 students in its BSc and MSc programs, which are based on AAU's problem-based learning model. The department leverages its unique
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problem-based learning model. The department leverages its unique research infrastructure and lab facilities to conduct world-leading fundamental and applied research within communication, networks, control
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development. Learn more about AAU Energy at www.energy.aau.dk . How to apply Your application must include the following: Application, stating reasons for applying and qualifications in relation to the position
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, or a related field. Have documented experience in some of the following: Computational materials modelling or quantum mechanical simulations (e.g. DFT, MD). Machine learning / deep learning (preferably