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Field
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optimal control approaches and conduct test-bedding • Collaborate with project partners and mentor junior researchers • Prepare project reports and publish research findings with industry engagement Job
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design and EDA research initiatives. Design, implement, and evaluate digital ICs using Verilog/SystemVerilog and related hardware description languages. Develop and optimize EDA workflows for processor and
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in the development, validation, and optimization of 3D-printed Ship Hull and Connector System. This includes conducting finite element modeling, ship resistance and stability assessments, as
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dynamic models from information gathered form live networks become essential to manage network requests, while maintaining high availability and optimal resource utilization. One Post Doctoral researcher
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reliability. The research will be conducted within the STRENGTHENS (Studies to Refine and Enhance Next Generation Therapies to Prevent Suicide) Group. STRENGTHENS focuses on developing, testing, and optimizing
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with the provisions of Decree-Law no. 66/2018 of 16th August, and all formalities established therein must be complied with at the signature of Fellowship contract. Working plan: Optimization
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Center for Drug Evaluation and Research (CDER) | Silver Spring, Maryland | United States | 1 day ago
to develop and apply data-mining tools Reviewing, extracting, and harmonizing data from literature Constructing and enhancing training databases for modeling purposes Learning to develop, validate and optimize
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that are relevant to industry demands while working on research projects in SIT. Job Details This Research Fellow will contribute to the UrEco 2030+ project: “Optimizing Urban Ecosystem Services Model for Urban
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optimization Signal processing and general communications background Programming skills in MATLAB and/or PythonGood writing and oral presentation skills, in English Eligibility requirements of MSCA: Research
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algorithms that significantly reduce computation cost, memory footprint, and power consumption. Design and optimize efficient training and inference pipelines for foundation models (LLM, VLM, VLA) across