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biomedical engineering, bioengineering, electrical and computer engineering, computer engineering, or other similar fields. The awarding of the fellowship is dependent on the applicants' enrolment in study
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-award courses of Higher Education Institutions. Preference factors: Machine Learning Knowledge. Knowledge of signal processing and machine learning libraries (e.g., PyCaret, scikit-learn). Minimum
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in biomedical image and signal processing; Previous experience in computer vision; . Research FieldComputer science » Computer systemsYears of Research ExperienceNone Additional Information Benefits
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tools to identify novel signaling pathways to develop new targets for drug discovery. Our research interests include: 1) Liver-gut and microbiota crosstalk as metabolic mediators in regulating both normal
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domain in the design of deep learning algorithms for cardiovascular disease detection. 4. REQUIRED PROFILE: Admission requirements: Master's degree in Biomedical Engineering, Computer Engineering
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, the ideal candidate should have experience in biomedical signal processing with prior publications on the subject. This role requires active collaboration with our Data Science team as well as with other
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and signal processing. Minimum requirements: Student in Biomedical Engineering or related areas. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria and corresponding valuation
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | about 8 hours ago
implantable sensors”, with reference COMPETE2030-FEDER-00781000, Operation No. 16631, funded by COMPETE2030 and national funds (FCT) under Call for Applications No. MPr-2023-12. Host Institution: i3S
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& Molecular Biology, the largest within the School of Biomedical Sciences at Monash University, is a national leader in its field. With a research and teaching focus spanning cell biology, signal transduction
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Job id: 123706. Salary: CLRF Point 9 to 12 £45,943-£52,291. Posted: 27 August 2025. Closing date: 07 September 2025. Business unit: Faculty of Life Sciences & Medicine. Department: Comprehensive