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25% teaching component. The position is dedicated to a Nepali case study. About the project UNRULY is dedicated to understanding uncertainty related to hydropower projects in the face of climate change
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Experience with high-throughput sequencing omics data analysis Proficiency in programming with Python, R, or C++ Desired: Familiarity with statistical and machine learning techniques. Knowledge about molecular
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that include an educational component including courses. This is the right position if you are highly motivated about fundamental science and excited about physics questions related to solid and fluid
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% teaching component. The Department teaches in all the sub-fields mentioned above. The successful candidate will be part of the Faculty’s PhD programme. The work is expected to lead to a PhD in political
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effects between the gut microbiome and drugs, and the impact on drug dosing. Relevant methods include pharmacokinetic investigations in patients, shotgun sequencing, bioinformatics, HPLC-MS analysis of drug
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selectivity of lipid transfer proteins. The project will exploit the wealth of available protein sequence and structure data through analysis using structural bioinformatics and molecular modeling tools, as
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data—into interpretable spatiotemporal risk models. A key methodological component could be the use of INLA for efficient inference in latent Gaussian models, and the candidate will contribute
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-lifetime Li-ion battery technology. In addition to cell testing and analysis, post-mortem material and electrochemical testing of battery components will be carried out to further analyze degradation
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for analysis of large-scale human genetic and neuroimaging data, to better understand how biological, psychological, and environmental factors contribute to severe mental and neuropsychiatric disorders
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theory, international relations and research methods. The appointment is for a fixed, non-tenured term of 4 years, and has a 25% teaching component. The Department teaches in all the sub-fields mentioned