301 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "UCL" "UCL" "UCL" "UCL" Postdoctoral positions in Denmark
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Job Description Are you passionate about data science and X-ray experiments? If so, this position might be perfect for you. We are seeking a data scientist to advance our analysis of complex data
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reference If you want a referee to upload a letter of reference on your behalf, please state the referee’s contact information when you submit your application. We strongly recommend that you make
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advanced modelling and techno-economic analyses of a potential CO2 hub at Nybro, with a particular focus on: Symbiosis between data centers and solid sorbent direct air capture (DAC) systems Integration
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: Establish and develop experimental protocols and pipelines and implement data management compliance. Presentation of your work in various meetings (locally at the department, national and international
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. Key activities include analysis of clinical and patient-reported outcome data, coordination of implementation studies in collaboration with ENT clinics, dissemination of results through peer-reviewed
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, which is a collaboration between the Department of Business Development and Technology and the Department of Digital Design and Information Studies. The project ‘Practice Resonant AI Ethics for the Public
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computer graphics, or human vision and attention. The posts require research skills in the design of studies, use of methods, research prototyping and data analysis, and you should have documented experience
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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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information For further information, please contact: Professor Torben Heick Jensen, thj@mbg.au.dk, phone +45 60202705 Application procedure Shortlisting is used. This means that after the deadline
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main areas of work: Exploration of heterogeneity in GDM risk and GDM subtypes and application of these insights to develop a GDM risk prediction model, based on data from The Danish Blood Donor Study