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the application process to the PhD programme Digitalisation and Society at Østfold University College when starting in the position. The appointment is to be made in accordance with the State Employees law, the act
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of the project is to 1) develop computational pipelines for image analysis and physical analysis of cell shape trajectories, and for combined morpho-molecular analysis of cell shape together with molecular markers
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: university degree in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry. Capability of team work is essential. Skills in high-performance computing, materials
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position as research assistant for up to 6 months before starting the PhD program. The position is available from 1st September 2025 or soon thereafter. Application deadline is 20. June 2025. Research
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interdisciplinary competences in: communication theory, networking, information theory, physics, mathematics, computer science, and statistics. This PhD project falls under Research Thrust RT3 on representation
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PhD position - Stress-testing future climate-resilient city and neighbourhood concepts (Test4Stress)
also supervised by Prof. Dr. Jana Sillmann, who is co-leading the Research Unit for Sustainability and Climate Risks (FNK). This Research Unit is devoted to inter- and transdisciplinary research and
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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
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modelling astrophysical phenomena. The PhD project will focus on developing theoretical methods to generate accurate data to meet this demand. The student will gain expertise in high-performance computational
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machines that will lead to demonstrations with practical relevance. Specifically, this project in the group of prof. Feringa aims to address two key challenges: 1) How can we amplify the work of molecular
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Worldwide Prof David Wagg Application Deadline: 30 April 2025 Details We are seeking an enthusiastic and self-motivated PhD student to join a collaborative project funded by EPSRC, working on an innovative