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data to develop a suite of national level vegetation indices capable of long term tracking and monitoring of vegetation quality, density, planting intensity and other suitable characteristics. Although a
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from date of hire. Preferred Qualifications Aptitude and experience with: (a) predictive machine and deep learning techniques, (b) statistical analysis, (c) hands-on experience using models such as
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Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill
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decision making, while you will be capable to apply machine learning and computational algorithms of social choice. This post is associated with following projects: Embedding EDI in the Distribution
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power engineering. In condition monitoring non-invasive data is analyzed through machine learning algorithms or by statistical methods. The aim of predictive analysis is to use non-invasive methods
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antigens, T cell receptor (TCR) and antigen interactions and their crucial role in anti-cancer immune responses. You'll leverage your strong background in computational biology, machine learning, and
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: Erlangen Programme for AI” This is a 5-year programme supported by the EPSRC and is a collaboration of mathematicians and computer scientists at the University of Southampton, the University of Oxford (lead
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26 Aug 2025 Job Information Organisation/Company INESC TEC Research Field Computer science » Computer systems Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 26
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power system models, addressing the challenges posed by increasing weather and climate variability in Ireland’s energy transition. The energy sector is deeply influenced by weather and climate. As Ireland
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, gender identity or expression, genetic information, HIV/AIDS status, military status, national origin, race, religion, sex, gender, sexual orientation, pregnancy, protected veteran status, or any other