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advanced AI algorithms to optimize and understand the optical properties of light-trapping surfaces. (more information can be found in the following News post ). You will work closely with colleagues both
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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 be working primarily with
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field
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Two postdoc positions on the ecology and physiology of microbial key players exposed to oxygen de...
and distribution of the above-mentioned microbes in oxygen-depleted environments Identification of the enzymes catalyzing the NO-dismutation reaction in AOA. Exploration of the physiological adaptations
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mechanism. Recent developments in protein structure prediction and protein de novo design have opened new possibilities for probing such mechanisms. The project will seek to use existing algorithms to new
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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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@bce.au.dk ) Position 3 – Biological CO2 Conversion Professor Largus (Lars) Angenent (l.angenent@uni-tuebingen.de ) Deadline Applications must be received no later than 7 August 2025. Application procedure