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School graduates over a thousand students who are ready to take on great ambitions and challenges. For more details, please view: https://www.ntu.edu.sg/eee We are looking for a Research Associate to
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operational support in the field of basic characterisation. Support operational, maintenance and training capability for analytical instrumentation, inclusive of thermal analysis, particle sizing, UV/IR
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 7 hours ago
social motivation, suicide and psychopathology risk, and childhood adversity using various methodologies in ages spanning 8-22. Applicants will primarily be involved in MRI data collection, analysis, and
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equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved
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associations with response to trauma and bereavement; 2) how genes influence risk for posttraumatic psychopathology; and 3) structural and cultural determinants of well-being and mental health in national and
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insight provided by the experimenter, using methods such as Proper Orthogonal Decomposition (POD) [8], spectral analysis, or Dynamic Mode Decomposition (DMD) [9]—which are currently being implemented in
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of the portfolio. Independent thinking and open dialogue are actively encouraged, with team members contributing to the skills, thinking, qualitative and quantitative analysis related to a range of the portfolio
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biomarkers for early detection, risk stratification, and treatment response, and by exploring new therapeutic strategies to improve patient outcomes. For more details, please view https://www.ntu.edu.sg
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assist with the evolution and deployment of the Digital Research cyber security maturity uplift. What you’ll do: Assist with the identification, initial analysis, and documentation of cyber security events
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analysis tools (e.g., bcftools, PLINK, SAIGE, GCTA). Develop and validate genetic risk models for cardiovascular diseases integrating genomic and clinical data across diverse populations. Methods include