37 experiment-"https:"-"https:"-"https:"-"https:"-"FEMTO-ST" PhD positions in Denmark
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. The position is fixed term and full-time and includes both research and teaching activities. The PhD scholarship is part of the research project Not Liking School: Lived Experience of School Emotions, funded by
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origin and type, transport history, season and plant/process conditions. Controlled experiments will quantify persistence, transfer and inactivation under representative transport, storage, cleaning
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PhD Scholarship in Development of Cement-Free Living Building Materials for Sustainable Construction
collaborators, providing opportunities to develop a broad scientific network and gain hands-on experience with complementary expertise and facilities. Responsibilities and qualifications As a PhD candidate, you
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applicants who demonstrate substantial hands-on experience implementing, training and evaluating deep-learning models will be considered. General interest in AI or experience limited to running tutorials
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framework of the project. Depending on the research question, possible methods could include qualitative fieldwork, interviews, case studies, surveys, experiments, or other relevant forms of data collection
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learning, computing, data science, biomedical engineering, or a related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with
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candidate will have expertise in several of the following areas: • Strong knowledge of ocean circulation, physical oceanography, and numerical ocean modelling. • Experience with regional ocean models
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international research environment. Preferred qualifications: Experience with human genetics, statistical genetics, or computational genomics. Experience analysing transcriptomic, epigenomic, single-cell, or
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questions, and be able to think critically and develop your own scientific ideas. Previous experience with machine learning, wearable sensors, haptics and control systems is an advantage but is not required
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background equips you to work with both materials and processes, and you are comfortable operating at the interface between experimental work and computational modelling. You have experience with Machine