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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 17 hours ago
pavement networks. This position will focus on modeling and optimizing pavement performance under evolving climate and hazard conditions. This position will advance modeling of pavement life-cycle
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energy systems and datasets. Validate and benchmark the developed models using building measurements, physics-based simulations and energy-system optimization models. Investigate how tabular foundation
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research teams: 1) The AI Group: Experts in systems, control, optimization, Large Language Model (LLM) training, domain adaptation, and instruction tuning, agentic AI orchestration, and reinforcement
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record to contribute to the development and automation of advanced electrolysis systems. The successful candidates will work on the automation, operation and optimization of electrochemical systems
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journals and presentations at conferences. - Collaboration with interdisciplinary research teams as part of the CERTAINTY project. - Optimization and documentation of modeling configurations for future
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design specific constructs to edit transcription factor genes and their target promoters, and analyse the effects of optimized gene expression regulation on plant performance under optimal and field-like
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system serving as a real-world lead-optimization case study. The successful candidate will play a central role in the computational and AI components of the project and work closely with our international
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Development Assists project leader with the development and implementation of research projects involving classical and molecular parasitology. Design, optimize, and validate nucleic acid-based assays
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, processing optimization, and experimental troubleshooting Materials characterization using techniques such as GIWAXS, Raman, FTIR, UV-vis, and electrical transport measurements Understanding structure-property
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multiple ship classes and shore power applications. The project seeks to deliver industry-relevant modelling toolkits that enable optimal design and operation of greener vessels, backed by real-world