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, enhanced by machine-learning and data-driven analysis techniques. Additionally, the study will encompass electrically triggered events that mimic the voltage-based signaling of biological synapses
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computational resources for data analysis. This position offers a dynamic, collaborative environment, engaging with experts across plant biology, microbiology, structural biology, and computational sciences and
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of existing ones for scientific applications; (ii) Large Language Models (LLMs) and multi-modal Foundation Models (iii) Large vision-language models (VLM) and computer vision techniques; and (iv) techniques
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.) and electrical device data analysis including transistor characteristics. You communicate effectively, verbally and in writing, evidenced by peer-reviewed publications and conference presentations
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and relevant data analysis. • Demonstrated experience in Python programming. • Knowledge of machine-learning algorithms. Additional Information: BNL policy requires that after obtaining a PhD
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to unique data sources, will ensure that the successful candidate has the necessary resources to solve challenging DOE problems of interest. The successful candidate will join a growing research group with
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facilities, as well as collaboration opportunities with domain scientists and security experts. Access to these platforms will allow computing at scale, and together with access to unique data sources, will
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data sources, will ensure that the successful candidate has the necessary resources to solve challenging DOE problems of interest. The successful candidate will join a growing research group with diverse