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of Research ExperienceNone Additional Information Eligibility criteria - Mass spectrometry; - Optics and lasers; - Physical and analytical chemistry; - Statistical analysis tools; - English language: C1 (Common
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for submission to funding bodies Strong analytical and computational skills in health data science Understanding of generative AI technologies in the development and enhancement of digital health tools Experience
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analytical techniques such as ANOVA, PCA, Regression, and Multidimensional Scaling (MDS). Experience in ecosystem service identification and analysis is highly advantageous. Excellent data management, research
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. Expertise is required or highly desired in one or more of the following areas: algorithms, analytical derivation, data analysis, coding, or mathematical modeling. Strong programming skills are highly desired
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analytical readouts, including immunohistochemistry, confocal microscopy, protein and RNA analyses, alongside fluid and tissue-based biomarker measurements to assess target engagement and pathway modulation
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: Preferably PhD in Computer Engineering, Computer Science, Electronics Engineering, or equivalent. Independent, highly analytical, proactive, and a team player; strong verbal and written communication skills
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(CEDRN). This role will focus on developing and piloting ED-based surveillance methods, generating high-quality data to inform public health decision-making, and advancing national capacity for future
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implement analytical pipelines for data preprocessing, quality control, normalisation, clustering, differential expression, trajectory inference, and pathway enrichment analyses. Integrate transcriptomic data
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regarding the collection and analysis of data collected in Global Control of HPV Related Diseases Research Program. Housed within the Faculty of Medicine, the School of Population and Public Health (SPPH) is
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, GenAI models act as probabilistic black boxes, often producing plausible but factually incorrect information without source attribution. This poses unacceptable risks particularly in high-stakes domains