21 phd-agent-based-modelling Postdoctoral positions at Brookhaven Lab in United States
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applies platforms for state-of-the-art techniques for Accelerated Nanomaterial Discovery, integrating synthesis, advanced characterization, physical modeling, and computer science to iteratively explore a
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Abilities: Experience with topological quantum materials High pressure processing including spark plasma synthesis Experience with dilution refrigerators Synchrotron based materials characterizations
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Knowledge, Skills, and Abilities: PhD in Chemistry, Physics, Biophysics, Biology, Biochemistry or Structural Biology. Proven ability to optimize peptide, protein or nucleic acid crystallization systems. Basic
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scientific and security problems of interest to BNL and the Department of Energy (DOE). Topics of particular interest include: (i) novel development of deep learning ML models and adaptation of existing ones
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year depending on performance and availability of funds. Candidates must have received a Ph.D. by the commencement of employment. BNL policy requires that after obtaining their PhD, eligible candidates
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investigators. Position Requirements Ph. D. in theoretical or physical chemistry, or a related field Extensive experience in one or more of the following areas: Computational modeling of homogeneous
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. The EIC will be a discovery machine for unlocking the secrets of the “glue” that binds the building blocks of visible matter in the universe. The machine design is based on the existing and highly optimized
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life – including the explosion of large language model (LLM) releases. BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications and uses
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industry, education, and public life – including the explosion of large language models (LLMs). BNL is engaged in numerous research efforts that employ NLP techniques for science and security applications
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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