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: This PhD project will develop model- and data-driven hybrid machine learning material models that capture the complex, nonlinear, path- and history-dependent behaviour of materials. The goal is to create
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will develop and carry out the project under the supervision of Dr. Senka Neuman Stanivukovic, Dr. Ksenia Robbe, and Dr. Florian Lippert. Together, they bring expertise in environmental humanities
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want to contribute to the next level of molecular computing? Are you excited about the application of AI tools to train molecular systems how to process information? Then join our team as a PhD candidate
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that field. Your most important activities in this position will be: Developing, improving and harmonising LCA methods, databases and tools to measure environmental impacts in projects in which clients
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deadline: 1 August 2025 Apply now In this PhD position, you will do research within the Biofabrication team with a specific focus on developing an engineered pancreatic endocrine construct to counter Type 1
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well as their cleanroom fabrication by silicon micromachining will be investigated. The main challenges are (1) the design and modelling of new sensor topologies, (2) development of the MEMS fabrication processes, (3
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full-time contract (100%) lasts four years, with the option to choose a part-time contract (80%) that lasts almost five years. In your PhD-research, you will: review literature, develop research
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PhD position on the transition to a green steel industry Faculty: Faculty of Geosciences Department: Department of Sustainable Development Hours per week: 36 to 40 Application deadline: 25
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to determine how PPE proteins mediate selective small-molecule transport and how structural insights into these outer membrane porins can guide drug development strategies to enhance compound uptake. Selection
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Description Join us in seeking exciting new developments using graph theory in nearest neighbor models for active matter! Do you enjoy working with graph theory, and seeing how functions on graphs can inform