The appointee will be responsible (a) assist in the development, training, and deployment of AI/Machine Learning models tailored for healthcare data; (b) support the integration and testing of IoT biosensors and remote monitoring devices; (c) collect, clean, and analyze clinical and health-related datasets; (d) collaborate with clinical partners to ensure technical solutions align with real-world healthcare needs; (e) contribute to academic papers, research reports, and grant proposals; and (f) manage day-to-day project logistics and documentation.

Applicants should have (i) a Bachelor's or Master's degree in a Health Science-related field (e.g., Biomedical Science, Health Informatics, Nursing, Public Health) with a strong quantitative background, OR a degree in Biomedical Engineering / Computer Science with a heavy emphasis on healthcare applications; (ii) strong programming skills in Python or R (experience with frameworks like PyTorch, TensorFlow, or Scikit-learn is highly preferred); (iii) solid understanding of Machine Learning, Deep Learning, or statistical modeling techniques; (iv) familiarity with IoT concepts, data acquisition, or sensor technology; (v) excellent written and verbal communication skills for cross-disciplinary collaboration (tech and health); (vi) prior experience in a research environment or writing academic literature; and (vii) strong problem-solving skills and a passion for digital health innovation.