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on diffusion and/or flow matching, that can rapidly adapt pre-trained models to new tasks and select optimally informative simulations at each stage in a design process. Collaborate closely with PhD students
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performance and durability at appropriate temperatures. Characterize materials using different techniques, and link properties to performance. Optimize reaction conditions and explore scale-up potential
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); Experience in mathematical modeling of cognition or behavior (e.g. optimality, drift-diffusion); Advanced computational and/or programming skills (Matlab, Python, C++, R, or other languages); A commitment to
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learning, with a focus on novel optimization techniques and memory architectures. Advancing the reasoning capabilities of large language models (LLMs). Developing methods to improve the safety and robustness
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such as insurance companies, pension funds and banks. This typically involves the development of new mathematical and statistical methods, or applications in optimal control and asset pricing. Do you
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will be determined in collaboration with you based on your strengths and interests, but could for instance involve developing new techniques for efficiently optimizing quantum computations, both in
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problems such as segregation, upward mobility, and political citizinship. What are you going to do Develop and optimize code packages on large scale multilayer network analysis Conduct research using large
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methodologies; You will characterise the materials using spectroscopic and surface characterisation techniques; You will identify and implement optimal methods for the integration and testing of materials in real
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those in a data- and compute-efficient manner to various problem settings. However, the perceptual possibilities are critically hindered by the language-focussed optimization of current foundation models