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-relativistic spin-splitting of the electronic band structure due to their magnetic order (including the collinear altermagnets). Our goal is to provide a test of theoretical predictions in a selection of real
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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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theoretical understanding and practical experience in deep learning-based machine learning. Strong research experience (e.g. evidenced by publication record). Excellent programming skills and in-depth
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) awarded within the last 5 years. Strong theoretical understanding and practical experience in deep learning-based machine learning and natural language processing. Strong research experience (e.g. evidenced
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mathematics, statistics) awarded within 5 years. Strong theoretical understanding and practical experience in machine learning, foundation models, and computer vision. Strong publication record in machine
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. in computer science or a related field (e.g., engineering, applied mathematics, statistics) awarded within the last 5 years. Strong theoretical understanding and practical experience in deep learning
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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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) – N/A Other Information: This is an on-site position One year term position with possible second year renewable BNL policy requires that after obtaining a PhD, eligible candidates for research associate
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choices Contribute to technical documentation and present results at internal reviews and conferences Required Knowledge, Skills, and Abilities: PhD in Physics, Accelerator Physics, Nuclear Engineering, or
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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