Research Fellow (Healthcare AI & Data Analytics)

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link - https://careers.nus.edu.sg/job/Research-Fellow-%28Healthcare-AI-&-Data-Analytics%29/34352-en_GB/?st=B140C17596AE89CB7E5418284380CB68EF28263D

We regret that only shortlisted candidates will be notified.

Job Description

The above position is now available to support the Principal Investigator, Assistant Professor Feng Mengling, for his research in the areas of healthcare data analytics and AI solutions.

Dr. Mengling Feng (https://www.mornin-feng.com/) is truly a cross-disciplinary scientists, who is currently a faculty member of the School of Public Health, School of Computing and School of Medicine, National University of Singapore (NUS). He is also the Senior Assistant Director working directly with the Chief Technology Officer (CTO) and Chief Medical Information Officer (CMIO) at National University Hospital (NUH). Dr. Feng is also an affiliated scientist with MIT. His research is to develop effective data analysis and machine learning methods to extract actionable knowledge from medical big data to improve the quality of care. Dr. Feng’s work was recognized by both well-established journals, such as Science Translational Medicine, and top international conferences, such as KDD, AAAI and AMIA.

Cross-disciplinary and International AI Lab

The selected candidate will be working in a cross-disciplinary team consists of data scientists, physicians, post-docs, PhD students and well respected faculty members from NUS, NUH and SGH. The candidate will be working on healthcare projects funded by our Ministry of Health, Health Promotion Board and AI Singapore. As Dr. Feng is an affiliated scientist, his lab constantly work with faculties and students from the Harvard-MIT Health Science Technology division. Dr. Feng has over 20 joint publications with Harvard and MIT between 2017 and 2019. He has also been organizing the annual NUS-MIT Healthcare AI Datathon (www.nus-datathon.com) , which were covered by many local news channels.

Potential Industrial and Overseas Exposure
Dr. Feng collaborates closely with various local and international industrial partners. Members in Dr. Feng’s team often have opportunities to work as affiliated scientists in our partnering companies, such as MSD, PingAn, Google, Intel, Nvidia, IBM, SAP, Philips, local and international start-ups.

Responsibilities and requirements
Major responsibility of the selected candidate is to apply and develop machine learning and AI technologies to solve healthcare challenges raised by our clinical collaborators. The selected candidate will also be involved in managing, extracting and pre-processing data for various projects.

This position will be initially available for one year. The grade of appointment will be accorded based on candidate’s academic qualifications and years of relevant experience.

Recruitment is open immediately, and will continue until the position is filled. Please submit the following during the application:
• Cover letter highlighting career goals and relevant experience
• Curriculum Vitae, containing details of three named referees

For further enquiries, please contact to Dr Feng at [email protected] or [email protected]

Qualifications

The successful applicant is expected to possess at least the PhD Degree in Computer Science, Engineering, Mathematics and preferably with relevant experience.

Required personal skills:
1. An independent and self-driven worker and a fast learner
2. Well-organized and has an eye for details
3. Excellent written and verbal communication skills
4. Ability to work effectively with colleagues to achieve team goals

Essential technical skills:
1. Excellent academic record
2. Knowledge and experience in statistical analysis or machine learning
3. Programming language: Python or R or C++

Good proficiency and experience in the following areas is a plus:
1. Experience with the PL-SQL/Trans-SQL
2. Knowledge and experience in GPU-based computation
3. Strong in Mathematics
4. Strong foundations in machine learning
5. Candidates with strong publication record in the field of machine learning are preferred