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seven hundred two euros) net, according to the table of monthly stipends available in the Regulations for Nova SBE Scholarships. SELECTION CRITERIA: The selection will be carried upon the evaluation
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progress reports, collating supporting materials, and ensuring timely submission to funding bodies. Assist researchers with data collection and analysis activities, including transcription, coding, and
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journals. Present research outcomes at national and international symposia, fostering knowledge exchange and networking within the global neuroscience community. Contribute to the development and delivery
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distribution networks, considering solutions such as FL Energy's OperatorFabric.; - Study human-machine interaction methodologies that reduce the complexity of supervising multiple distribution networks
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cross-regional logistics network scenarios, data collection and development of decision support models for optimal maritime infrastructure for collection of the captured CO2 from the emitters and
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, an extensive scientific network, and an interdisciplinary curriculum about the origin and prevalence of life. The NOMIS Foundation supports and enables insight-driven science across all disciplines
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adjusting the plan for the project as needed Emphasis will be placed on personal qualities. We offer Being part of, AI LEARN, an exciting nationwide network of researchers An exciting job with an important
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adjusting the plan for the project as needed Emphasis will be placed on personal qualities. We offer Being part of, AI LEARN, an exciting nationwide network of researchers An exciting job with an important
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: The net monthly allowance is 1309.64€, according to the table of values of the scholarships awarded directly by FCT, I.P. in Portugal. Payment will be made monthly by bank transfer. If the fellowship holder
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Koziarski Lab - The Hospital for Sick Children | Central Toronto Roselawn, Ontario | Canada | 2 months ago
focus on developing generative models for small molecule design. The candidate will contribute to the development of chemistry-informed generative models using frameworks such as generative flow networks