The posting
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-AssistantAssociate-%28AIML-and-Medical-Image-Analysis%29/31120-en_GB/
We regret that only shortlisted candidates will be notified.
Job Description
The National University of Singapore invites applications for a Research Assistant (RA) position in the Computational Brain Imaging Group (CBIG) at the Yong Loo Lin School of Medicine.
Our group develops computational methods and machine learning approaches to understand brain organisation, how it supports cognition and behaviour, and how it changes across the lifespan. Drawing on large-scale neuroimaging data, we investigate fundamental principles of healthy brain development and ageing, and how brain structure and function are altered in neurological and psychiatric disorders.
Joining CBIG offers the opportunity to contribute to questions at the intersection of neuroscience, artificial intelligence, and medical imaging. You will work within a collaborative, interdisciplinary team, with access to high-performance computing resources and a network of scientists and clinicians in Singapore and internationally. You will receive close mentorship to strengthen your research skills and contribute to scientific publications.
This is a full-time position based on site in Singapore. Appointments will be made on a two-year contract in the first instance, with the possibility of extension. The position is available immediately, with a preferred start date no later than January 2027.
Purpose of the post
We seek an enthusiastic and self-motivated Research Assistant with a strong computational background to work closely with Dr. Sina Mansour L., A/Prof. B.T. Thomas Yeo, and their collaborators to develop and apply computational approaches to advance our understanding of Alzheimer’s disease.
The position will involve developing, implementing, and evaluating state-of-the-art computational pipelines for medical image analysis and machine learning. These pipelines will be used to study Alzheimer’s disease and identify biomarkers for diagnosis, prognosis, and treatment response, with the aim of advancing personalised care. The role requires interdisciplinary expertise, drawing on ideas from engineering, mathematics, and computer science to shed light on the biological mechanisms, brain changes, and cognitive and neuropsychiatric manifestations of Alzheimer’s disease.
The RA will have the opportunity to develop and lead an independent research project under close mentorship, while contributing to other collaborative lab initiatives. Previous RAs have published first-author studies and progressed to graduate programmes at universities including Stanford, Cornell, and Oxford.
Main duties and responsibilities
- Develop, implement, and evaluate computational pipelines for neuroimaging analysis and machine learning in Alzheimer’s disease research.
- Manage, preprocess, and quality control of large-scale neuroimaging datasets and associated clinical and behavioural data.
- Apply computational and statistical methods to characterise disease heterogeneity and evaluate candidate biomarkers.
- Develop research workflows and contribute to software, code repositories, and documentation.
- Lead an independent research project under mentorship, while contributing to collaborative lab initiatives.
- Communicate findings through scientific manuscripts, data visualisation, presentations, and discussions with collaborators.
Qualifications
Essential:
- A bachelor’s or master’s degree in computer science, engineering, computational neuroscience, biomedical engineering, or a related discipline, with substantial computational training or research experience.
- Demonstrated programming proficiency, preferably in Python, and the ability to develop, debug, and maintain analytical code.
- A solid foundation in quantitative methods, including statistics, mathematical modelling, or machine learning.
- An interest in applying computational approaches to biological and clinical questions, and a willingness to learn across disciplines.
- Good written and verbal communication skills, with the ability to work independently and collaborate within an interdisciplinary team.
- An organised, reliable, and self-motivated approach to research.
- Availability to commit to the position for at least two years.
Desirable:
- Experience with medical imaging or neuroimaging data analysis tools used for preprocessing, quality control, or quantitative analysis.
- Experience developing or evaluating machine learning models, including assessing their robustness and generalisation.
- Familiarity with Linux, shell scripting, high-performance computing, and version control tools such as Git.
- Experience building reproducible analytical pipelines or contributing to open-source software.
- Familiarity with Alzheimer’s disease, brain ageing, or related neuroscience research.
- Previous research experience, demonstrated through a dissertation, research project, publication, or relevant software contribution.
Interested applicants are invited to email a brief cover letter, a CV, and contact details for two referees to NUS Career Portal. The cover letter should outline their research interests, relevant experience, and earliest possible start date.
Applications will be reviewed on a rolling basis until the position is filled. We thank all applicants for their interest; only shortlisted candidates will be contacted.
