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Electrophysiological characterization of muscle fiber excitability (in collaboration with the research group) In vivo studies using animal models of neuromuscular disease Integration of molecular and transcriptomic data
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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paths at DTU here . Further information Further information may be obtained from Professor Julia Kirch Kirkegaard (jukk@dtu.dk ) and/or Section Head Tanja Schneider (tansch@dtu.dk ). You can read more
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to diversity and inclusion, and success in mentoring. Place of work The place of work is the Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark. Contact information
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processing historical data, and the tasks will be relevant to the your further course of study. We are looking for a student who: Has strong quantitative skills Is proficient in Excel, Stata, and either R
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to diversity and inclusion, and success in mentoring. Place of work The place of work is the Department of Food Science, Aarhus University, Agro Food Park 48, 8200 Aarhus N, Denmark. Contact information
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employment is 21 months. Expected starting date is 1 June 2026, or according to mutual agreement. You can read more about career paths at DTU here . Further information Further information may be obtained from
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publications in leading international venues. - Guiding and working with Master and Ph.D. students at ECE and collaborators as needed. More information - see the attached link or email: sshreya AT ece.au.dk
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evaluation using nasal epithelial models and tissue Contribute to in vivo validation in an established mouse model of acute seizures Analyze pharmacokinetics, biodistribution, and therapeutic efficacy data Co
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industry-facing research collaboration and coordinate cross-partner workflows in planning, data-sharing, and iterative decision-making across industrial and academic stakeholders. Teach and supervise PhD