"Research Fellow (CBDS/SES)"

Job Description

The Duke-NUS Centre for Biomedical Data Science (CBDS) serves as a central hub for Duke-NUS faculty specialising in Biostatistics, Bioinformatics, Systems Biology, Artificial Intelligence (AI), and other quantitative and data-driven sciences. CBDS functions as a strategic platform for cutting-edge research, education, and services in data science, AI, and biomedical computation, building on existing institutional initiatives such as DAISI.

We are hiring two Research Fellows for a 2-year contract. This position is part of an exciting project developing AI-based models to predict cognitive decline in patients with cognitive impairment. The role emphasises computational and AI methodologies to analyse multimodal data, enabling early detection and personalised interventions in clinical neuroscience.

The candidate will take the lead on machine learning and computational analyses, primarily supporting our translational research program focused on developing AI-based models to predict cognitive decline. This role offers the opportunity to collaborate with clinicians, data scientists, and the broader research community within SingHealth and Academia campus, contributing to high-impact advancements in personalised medicine for cognitive health.

• Independently carry out the development and validation of ML-based predictive models using multimodal data (neuroimaging, clinical, biomarker, and demographic).
• Design and implement computational pipelines, statistical and machine learning methods for data preprocessing, analysis, visualisation, and model deployment, leveraging baseline and longitudinal datasets from Singapore and Southeast Asian cohorts.
• Provide support for external grant/protocol development, study design, management of research activities, and prospective data collection for model validation and fine-tuning.
• Manage and maintain databases of processed datasets for use by internal and external stakeholders, ensuring data integrity for real-time predictions and cost-effectiveness analyses.
• Participate and present in lab meetings, local and international conferences, and contribute to high-impact publications.
• Provide guidance and mentorship to undergraduate/medical students and research assistants.
• Develop and deploy user-friendly tools, such as R Shiny applications, for clinical translation of predictive models.
• Perform other related duties as required.

Job Requirements

• Ph.D. in Computer Science, Machine Learning, Biomedical Engineering, Electrical Engineering, Statistics, Data Science, or related fields.
• Proven publication record in reputable journals.
• Strong expertise in deep learning, artificial intelligence, and machine learning methodologies, with high competency in Python and R programming languages for modeling complex biological data.
• Preferably experience with medical imaging analysis, particularly MRI data processing and interpretation.
• Keen interest in translational research that bridges AI with clinical neuroscience applications.
• Excellent organisational skills and meticulous record-keeping.
• Proven ability to work effectively in a collaborative, multidisciplinary team.
• Strong critical thinking, communication, and presentation skills.
• Able to prioritise, multi-task, and work independently in a diverse research environment.

We regret that only shortlisted candidates will be notified.

More Information

Location: Outram Campus

Organization: Duke-NUS Medical School

Department: Office of Research

Employee Referral Eligible: No

Job requisition ID: 31759

Contact List for further enquiries

Hiring Manager: Seyed Ehsan Saffari

Hiring Manager Email: GMSSES@nus.edu.sg

Apply now