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well as by the Regulations for Grants of INESC TEC and for https://files.dre.pt/2s/2019/12/241000000/0009100105.pdfFCT Grants Regulation in force. For more information, please check the Regulations for Grants
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For disease Interception) (https://www.edent1fi.eu ). The research fellow is sought to support the UK component which is linked to the existing T1D screening program scaled up nationally by the Department
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supervisor: The final report model to be prepared by the fellow is available at the following link: https://ucppt-my.sharepoint.com/:w:/g/personal/ccabral_ucp_pt/ESnbf2LTfxFGj8NsKVEAe3IBi00sddFg238l4P7ziYmXTw
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of their development and structure. Working closely with colleagues at the Universities of Leeds and Reading, you will integrate theoretical understanding, observational data, and modelling approaches to improve
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data, inspection results and carbon footprint information. Develop, train and validate AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks
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Regulation in force. For more information, please check the Regulations for Grants of INESC TEC and relevant annexes at www.inesctec.pt/bolsas Where to apply Website https://www.inesctec.pt/en/opportunity
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 2 months ago
Fellow to work on the project entitled ‘Small-area attitude mapping’ which involves the compilation of Australia attitudinal survey information, small-area modelling of demographic characteristics, and
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analyzing hyperspectral data and developing machine learning models - Genetic or molecular lab experience - Bioinformatics, or statistical genetics experience - Excellent written and oral communication skills
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information, please check the Regulations for Grants of INESC TEC and relevant annexes at www.inesctec.pt/bolsas Where to apply Website https://www.inesctec.pt/en/opportunity/AE2026-0214 Requirements Research
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scientific programme is integrated across three scientific work packages, where data, technologies and biological models will be shared across projects through joint supervision, network activities and