25 software-engineering-model-driven-engineering-phd-position Postdoctoral positions at Brookhaven Lab
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for scientific and security applications; (ii) ML model optimization for inference speed and deployment for real-time analysis; and (iii) AI model training for analog in-memory computing. The position provides
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the department on new potential collaborations. Position Requirements: Required Knowledge, Skills, and Abilities: Ph.D. in computer science or a related field (e.g., engineering, applied mathematics, statistics
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, and readout electronics. POSITION DESCRIPTION Experimental and practical Quantum Information Science and Technology (QIST) is a key area of R&D for BNL. The successful candidate will join a fast-growing
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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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, safeguards, and healthcare. The Group is heavily involved in engineering design, modeling, testing, and field deployment of radiation detection systems to support sponsors in their operation and research. In
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associate position with a focus on national security applications of natural language processing (NLP). This extremely fast-moving and competitive field has produced innovations with highly visible impact in
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and national challenges. Position Description The Electron-Ion Collider (EIC) project is seeking an accelerator physicist at the postdoc level to join the accelerator design team. Core duties are
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to perform experiments using low voltage (<50 V) electrical equipment OTHER INFORMATION: This position is on-site. BNL policy requires that after obtaining a PhD, eligible candidates for research associate
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Apply Now Job ID JR101725Date posted 04/01/2025 Position Description: The Postdoctoral Research position would be part of a Department of Energy funded Energy Frontier Research Center, the Center
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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