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Faculdade de Ciências Médicas|NOVA Medical School da Universidade NOVA de Lisboa. | Portugal | 3 days ago
for the preparation and implementation of the project activities. Duration and start date The fellowship will have an initial duration of 6 months, with an estimated start date of March 1, 2026. The fellowship contract
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microelectronic hardware. Preclinical in-vitro and in-vivo testing of devices and methods will allow real world validation of this unusual Brain-Computer Interface. More information: (7) BRAINET: Overview
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Administration Analyst position works with the Center on Education and Training for Employment (CETE) Information Technology Staff to ensure computer equipment can optimally support the work of the Center
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Regulations. Where to apply Website https://apply.uc.pt/ Requirements Research FieldEngineering » Computer engineeringEducation LevelBachelor Degree or equivalent Additional Information Work Location(s) Number
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: https://www.fct.pt/wp-content/uploads/2025/02/Tabela_valores_SMM_2025.p… )), supported though PAD no. C69621 and C69622. 8. SELECTION METHODS AND COMPOSITION OF SELECTION BOARD The selection method
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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significant time in preparing and analyzing firm- and firm-worker-level data to study the above topics. A full job description is available at https://web.mit.edu/sloan-hr/jobs
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. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. Job Type: Officer of Administration Bargaining Unit: Regular
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Experiment (PRIDE) Doppler/VLBI data: open-source analyses in orbit estimation and ephemeris improvement. Job description We are seeking a highly motivated PhD candidate to strengthen the scientific
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion