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-term carbon cycle and over the coming century. This PDRA position will focus on model approaches to quantifying CO2 exchanges associated with chemical weathering associated with the warming cryosphere
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of 24 months. The project aim’s to develop new constitutive models to describe the mechanical behaviour of Thermoplastic Elastomers (TPEs). These polymers are increasingly being developed as a
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on and defensive mechanisms for safe multi-agent systems, powered by LLM and VLM models. Candidates should possess a PhD (or be near completion) in Machine Learning or a highly related discispline. You
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(e.g., Reinforcement Learning, Agent Based Modelling) to join our team full-time as part of a large international collaboration of European researchers (incl. Tobias Dienlin, Veronica Kalmus, Adrian
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. Desirable criteria Track record of interdisciplinary collaboration. Familiarity with cognitive architectures or agent-based modelling frameworks. Ability or potential to contribute to the development
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on evaluating the abilities of large language models (LLMs) of replicating results from the arXiv.org repository across computational sciences and engineering. You should have a PhD/DPhil (or be near completion
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. Desirable criteria Experience working with generative models or large language models Experience with GPU-based model training or cloud computing Knowledge of synthetic biology or regulatory sequence design
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structural maintenance of chromosomes (SMC) complexes shape chromosomes by DNA loop extrusion, how they cooperate with DNA topoisomerases, and how bacteriophages and other infectious agents manipulate host
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PhD in a relevant scientific discipline, for example, Cell Biology-related subject, Tissue Engineering or Biomaterials. Excellent manual dexterity and experience in cell culture and models, and tissue
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design, and agent-based modeling to address problems in psychological domains, with a particular focus on applications in anxiety disorders and meta-scientific/methodological questions in psychological