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development. Experience with implementing statistical learning or machine learning (e.g. Bayesian inference, deep-learning). Programming skills in Python and experience with frameworks like PyTorch, Keras, Pyro
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. The application should contain a cover letter (maximum 1 page) describing the applicant’s research interests, an updated CV with a list of publications, copies of diplomas and certificates of higher academic
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) describing the applicant’s research interests, an updated CV with a list of publications, copies of diplomas and certificates of higher academic degrees as well as contact details (name, e-mail, phone number
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-on experiments (prior bench experience a plus). Evidence of outreach, mentoring, or community building. Required documents for your application: Cover letter explaining why you want to join the team Update CV
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documents for your application: Cover letter explaining why you want to join the team Update CV Contact information of three referees Open Position (published): 08/08/2025 End Published: 30 /09 / 2025
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on research activities with team members and external partners Stay updated with relevant literature and methodologies, maintain and share accurate records of findings with the team Present findings to the team
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emerging new insights in the literature, you will update the experimental strategy and carry out all the experimental work, supported by technical staff and specialists on the respective instruments. You
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progress. Continuous Learning and improvement: Willingness to stay updated with the latest advancements in road condition research, tire technology, data analysis techniques, and industry trends. Actively
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the training activities and scientific events, in coordinating and updating a scientific blog on legislative and jurisprudential developments and in maintaining contact with DTU-GREITMA's stakeholders Helping
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responsibilities: PIK is seeking a qualified junior researcher or postdoctoral scientist responsible for the estimation of future fire risk with the use of the updated SPITFIRE model, based on future projections of