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directions include: ● Generative models of cell–cell communication . Move beyond descriptive ligand–receptor analysis to models that predict and help understand how cells react to signaling cues. ● Joint
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of food web components, from primary producers to fish, during open-water (summer) and under-ice (winter) conditions. Analysis of biomarkers (PUFA and cyanotoxins) in biological samples using
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for the processing, analysis and interpretation of large volumes of scientific data, as well as to the integration of artificial intelligence-based tools into highly technologically complex research environments
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(fluid dynamics) is highly beneficial Experience with statistical analysis, coding (R or Python), and digital modelling strongly preferred Willingness to travel (minimum to UK for experimental work
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analysis to better understand how molecular and cellular processes are coordinated across cells, tissues, and organ systems in human health and disease. You will be responsible for developing and applying
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control, proximity engineering and quantum transport. Analysis and interpretation of experimental data. Presentation of results at international conferences and preparation of scientific publications
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example through relevant work experience and/or peer-reviewed academic works. You must have excellent written and oral English skills You must have good programming and data-analysis skills, for example in
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must have excellent written and oral English skills You must have good programming and data-analysis skills, for example in Python, MATLAB, R or equivalent You must have relevant knowledge or experience
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investigate CO₂ desublimation under controlled cryogenic conditions. The project is primarily experimental, supported by modelling and data analysis. You will design, build and operate a cryogenic experimental
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, provide only limited insight into how such interference behaves at system level. In this PhD project, you will develop the measurement and analysis methods needed to make these environments observable. You