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) exhibit compositional failures that strikingly parallel known human cognitive constraints, such as the binding problem. The geometric overlap of concept vectors in latent representation space correlates
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training approaches to maximize the productivity and efficiency of your time in the laboratory. You will be provided with hands-on training in the lab, while being given space and freedom to develop your
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feature spaces to find out-of-distribution atomic environments Use chemical neighborhood representations to detect sparse or unseen cases Combine ML features with chemical descriptors to enhance uncertainty
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particular, we will explore novel interfaces between PICs and free-space optical technologies. This will open up new avenues to guide the flow of optical information from the environment into PICs, where it
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process and equipment optimisation Application of artificial intelligence, surrogate modelling, and optimisation methods to accelerate exploration of RAM design and operating space. By coupling simulation
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signatures in communication and coordination data predict collective outcomes — such as group spacing changes, behavioural synchrony, and leadership transitions — beyond what pairwise models capture
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of chemistry, structure, and transformations at the atomic scale of buried interfaces and defects by correlated experimental techniques in both space and time (e.g., correlated APT, TEM, FIM, EBIC, EBSD, XPS
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, including Laser Interferometer Space Antenna (LISA), Einstein Telescope, Square Kilometre Array Observatory (SKAO), and NANOGrav. This involvement will enable them to compare theoretical predictions directly
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compensation hours. Flexible working hours, a home office allowance, and the option to work from home. Freedom and space to shape your work independently and develop your ideas. A close-knit community of
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shape the project’s success: Adversarial attack development: you will design and implement problem-space adversarial attacks against LLM-based vulnerability detection systems. Robustness evaluation