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start to finish. Specifically, the project will combine 30 years of Danish health data at the service of hundreds of women with endometriosis, recruited through online platforms. It will use AI-enhanced
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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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, and train deep learning models on the resulting data to design new antibiotic compounds that evade both current and likely future resistance mechanisms. Your computational work will directly steer
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: A Ph.D. in biophysics An Msc in physics. Extensive research experience in soft matter and biophysics. Analytical and programming skills for data analysis and ai-based analysis. Good interpersonal and
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on modelling the effects of small insertion and deletions. The candidate will also help with data management tasks for the database of variants effect that we are maintaining at DTU. We are looking for a
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use the algorithms in practice, when little to no assumptions can be made on the data. Required Qualifications PhD in computer science, mathematics, statistics, or related fields (by the start date
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structures. You will work closely with computational researchers to gather data, evaluate AI predictions, and design experiments. You will work in a team with 7 PhD-students and 4 postdoctoral researchers and
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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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The Department of Digital Design and Information Studies within the School of Communication and Culture at Aarhus University invites applications for a postdoctoral position in practice-based
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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