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/2019, of 28 August; Regulation of Research Grants of the FCT (https://www.fct.pt/en/media/noticias/novo-regulamento-de-bolsas-de-inve… ). Work Plan: RESEARCH SCHOLARSHIP– the work plan is developed
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optimization and resource allocation schemes and algorithms for link and network optimization with hybrid fibre-FSO-RF communications. You will further augment software defined networking controllers
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subjective assessment. Design and implement machine learning algorithms for real-time prediction of occupant thermal comfort. Analyse physiological signals including skin temperature, skin conductance, heart
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of accomplishments (e.g., peer-reviewed publications and/or patents). Key Responsibilities & Accountabilities: Algorithm Development, Data Analysis and Communication: Effectively design, implement, and evaluate
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expanding the Food Compass algorithm according to the latest science, including expansion to include novel health-related bioactive attributes; Supporting ongoing work and manuscripts, including related data
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structures, algorithms, computer architecture, operating systems and databases) to develop and write original software to meet research-based needs. Utilizes experience of scientific and mathematical concepts
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growth of the Illinois Tech Mumbai academic programs Special consideration will be given to candidates with teaching or research interests in: Algorithms Science of Programming Computer Vision Machine
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& Engineering, or a closely related engineering discipline, with strong emphasis on high-fidelity CFD Experience in advanced CFD solver development, algorithm improvement, and numerical methods for highly coupled
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, extensive computing resources and close day-to-day supervision within the group. Tasks and responsibilities: include developing reconstruction algorithms for the muon bundles recorded by KM3NeT; extracting
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the PORTUGAL2030 Programme, under the following conditions: Work Plan and Objectives to Reach: The work to be carried out aims at the research and development of Computer Vision and Machine/Deep Learning algorithms