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Degree Dr rer pol Course location Frankfurt am Main Teaching language English Languages The doctoral programme at Frankfurt School is entirely in English. Full-time / part-time full-time Programme
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completed Master´s or equivalent university degree, ideally in the life or natural sciences working experience with Amphibians or other aquatic vertebrates, fluorescence microscopy, and behavioral experiments
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Duration of Studentship: Full-time – 3 Years Start Date: 1 October 2025 Application Deadline: 29 August 2025 Primary Supervisor: Professor Peter Munro (p.munro@ucl.ac.uk ) Secondary Supervisor
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structure, reactivity, and stability. - see comment You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Approval and
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lead to a dissertation (PhD thesis). We will draft an educational plan that includes attendance of courses and (international) meetings. We also expect you to assist in teaching undergraduates and master
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: virus cultivation, infection of cells, cloning; cultivation of eukaryotic, transformed cell lines as well as primary cells; fluorescence microscopy, super-resolution microscopy, expansion microscopy, flow
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industrial partners in Denmark as well as abroad. Your primary tasks will be to: Advance research in all aspects of the CO2 value chain Supervise and inspire students at all levels Procure research funding
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Collaborative Doctoral Project (PhD Position) - AI-guided design of scaffold-free DNA nanostructures
nano-structures. In this project, we will combine numerical models, experiments, and artificial intelligence (AI) to guide the design of specific DNA nanoconstructs. The primary goal is to build an AI
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a team of 25 colleagues dealing with CCUS, and industrial partners in Denmark as well as abroad. Your primary tasks will be to: Apply AI in context of capture solvent modelling Understand and analyse
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approaches, including principal component analysis and machine learning, to handle multivariate datasets. Prior experience in data science is not essential; the successful candidate will be supported through