Job Description

Research Associate (Master’s level) positions are available immediately in the Department of Biochemistry, National University of Singapore, in collaboration with the Bioinformatics Institute (BII), A*STAR, under the AI-based Digital Pathology (AiDP) Programme. The programme focuses on the development and validation of advanced AI methodologies, including image processing, computer vision, and mathematical modelling, for cancer diagnosis and prognosis using digitised pathology slides. These include both biopsy specimens and standard whole-slide images.

The innovative AI-based Digital Pathology Diagnosis (AIDP) programme is a pioneering venture set to transform the landscape of AI pathological diagnosis and solve the global shortage of pathologists and increasing cancer cases with cutting-edge AI technologies. Our focus is on bridging gaps in data quality, model generalizability and market scalability. This groundbreaking initiative aims to advance pathology practices by developing artificial intelligence systems that accurately diagnoses cancer and other diseases from digital pathology images. By leveraging state-of-the-art AI technology and advanced methodologies, we strive to achieve breakthroughs that will revolutionize the way pathologists diagnose diseases, such as Lymphoma, Gastric, Colorectal and Breast cancers, ultimately improving patient outcomes and healthcare efficiency. This program is supported by national funding and led by esteemed institutions/hospitals and cross-disciplinary leaders in the field, providing an unparalleled opportunity for professional growth and collaboration with top-tier experts.

We are seeking passionate, talented individuals to join our dynamic team. If you are driven by curiosity and have a desire to be at the forefront of AI medical innovation, this is the perfect opportunity for you. As a member of our team, you will work in a stimulating environment where creativity and initiative are highly valued. You will have access to state-of-the-art facilities, high-quality data and other resources, and the chance to contribute to high-impact research that can shape the future pathology. Our focus is on creating robust, reliable AI systems that can assist pathologists in making faster and more accurate diagnoses, ultimately leading to better patient care and improving the life quality of humankinds. We are looking for candidates who are not only skilled but also enthusiastic about making a difference. Join us in this exciting journey and be a part of something truly extraordinary!

Qualifications

General Requirements:

• Highly motivated researcher with an M.E. or M.Sc. degree, eager to pursue a scientific career, particularly with a passion for artificial intelligence, machine vision, computer vision and biological image processing projects.
• Independent thinker with a strong passion for advancing the field of AI and biological image processing in clinical diagnosis.
• Excellent team player capable of conducting independent research under the guidance of the Principal Investigator (PI) and collaborating effectively with lab members.
• Solid general knowledge and understanding of scientific and engineering principles.
• Exceptional scientific and technical writing skills, coupled with outstanding communication abilities.
• Previous experience in medical image analysis projects, whether in an industrial or academic setting, is a plus but not mandatory.

Specific Technical Requirements:

• Proficiency in one or more programming languages, such as Python, MATLAB, C/C++, or Java, with strong emphasis on scientific computing and AI model development.
• Solid theoretical foundation and practical experience in artificial intelligence, machine learning, pattern recognition, and digital image processing, particularly in biomedical or histopathology applications.
• Hands-on experience in designing and implementing deep learning models for pathology images, including classification, segmentation, and representation learning.
• Strong interest and experience in Explainable AI (XAI) techniques, such as saliency maps, attention mechanisms, feature attribution, concept-based explanations, uncertainty estimation, and model interpretability frameworks.
• Familiarity with deep learning frameworks such as PyTorch, TensorFlow, or equivalent, including model training, evaluation, and deployment.
• Experience in developing or applying explainability and validation methods to assess model robustness, bias, and generalisability in clinical contexts.
• Ability to implement numerical and computational algorithms efficiently, with attention to reproducibility and software engineering best practices.
• Strong analytical and logical reasoning skills to formulate, analyse, and solve complex, multi-disciplinary scientific problems.
• Basic knowledge of cell biology, pathology, or histological principles is an advantage, particularly for interpreting AI explanations in a clinically meaningful manner.
• Ability to learn quickly and integrate knowledge across AI, pathology, and clinical workflows.
• Experience or strong willingness to collaborate closely with hospitals, pathologists, and clinical researchers, incorporating domain feedback into model design and evaluation.
• Strong communication skills, including the ability to present research findings clearly at internal meetings, seminars, and international conferences.
• Proven scientific writing skills, including preparation of technical reports, grant-related documentation, and peer-reviewed journal publications.
• Familiarity with research software practices, such as version control (e.g. Git), experiment tracking, and reproducible research pipelines, is desirable.

Please email a detailed CV containing a list of publications to Prof. Kenneth Ban ( kenneth_ban@nus.edu.sg ) and Prof. YU Weimiao ( yu_weimiao@a-star.edu.sg ).

We regret that only shortlisted applicants will be notified.