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, or similar languages for data analysis Proficiency in scientific English (written and spoken) is a must, German and/or French is an advantage Willingness to spend several months at other institutions abroad
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instruments (e.g. Thermo Orbitrap technology). Experience in using (AP-)MALDI technique for analysis and imaging. Experience in LC/MS for targeted or untargeted studies is an asset Ability to execute research
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in a number of the following topics: Turbulence modeling with wave propagation simulations Modulations used in optical wireless communications Data Analysis and Management Implement and open-source
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, and multi-level data analysis Communicate and collaborate with a research team, including teachers and student assistants Engage in international opportunities for learning and development (i.e
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AI agents themselves. The candidate will explore behavioural analysis techniques. Another research questions is related to the definition and application of a unified policy through both legacy IT
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to evaluate. The main research question is how to automatically harmonize the retrieved information allowing a unique analysis and to map them against multiple user-tailored outputs. This is necessary as the
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datasets such as the Luxembourg Parkinson’s Study and different prodromal cohorts for neurodegenerative diseases are ready for analysis. The doctoral researcher will: Conduct research that will compose a PhD
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photopolymerization of the precursor. The practical work will be complemented by fluid mechanics computer simulations, including solutions employing machine learning, and theoretical analysis using Leslie-Ericksen
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into cross-seeding between microbiome-borne amyloidogenic proteins and human proteins implicated in neurodegenerative disea Your responsibilities: The doctoral candidate will perform computational analysis
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computational models and data analysis code to process large, multimodal behavioral datasets using both traditional methods (e.g., factor analysis) as well as more modern approaches (e.g., deep learning