55 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"UNIV" positions at Nature Careers in Denmark
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departments. Contact information For further information, please contact: Dr., Peter Zeller, peter.zeller@mbg.au.dk Deadline Applications must be received no later than 23 February 2026. Application procedure
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? Then the Department of Electrical and Computer Engineering invites you to apply for a 2 year postdoc position bridging research with industrial implementation and innovation. Expected start date and
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analysis) Data collection, documentation, and basic data analysis Contribution to reporting, presentations, and potentially scientific publications Supporting collaboration within the research group and with
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sets, lexicon development, use of instrumental techniques to correlate or predict sensory characteristics and multivariate data analysis. This position is part of an interdisciplinary research project
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as of that date be with a department Contact information For further information, please contact: Prof. Alfred Spormann, aspormann@inano.au.dk. Application procedure Short-listing is used. This means
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research sections with around 350 highly skilled employees, of which approximately 50% are scientific staff. More information can be found here . We believe in encouraging inclusion, acceptance, and
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Faculty position in Molecular Health (Tenure-Track Assistant Professor / Associate Professor) at ...
employment is Aarhus University with related departments. Contact information For further information, please contact: Head of Department, Claus Oxvig. Phone number: +45 30362460 Email: co@mbg.au.dk Deadline
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to the faculty’s departments. Consequently, your employment will as of that date be with a department. Contact information For further information, please contact: Professor Troels Skrydstrup, +45 28 99 21 32, ts
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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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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