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 a strong emphasis on scientific computing and algorithm development.
• Extensive knowledge and hands-on experience in artificial intelligence, machine learning, pattern recognition, and digital image processing, particularly for biomedical or histopathology applications.
• Demonstrated ability to design, implement, and optimise numerical and computational algorithms, with attention to robustness, reproducibility, and performance.
• Solid understanding of computer vision techniques relevant to cellular and subcellular analysis, such as image segmentation, object detection, feature extraction, and quantitative measurement.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, or equivalent, including model training, evaluation, and deployment.
• Familiarity with quantitative biomarker analysis, including intensity normalization, spatial localization, and expression scoring; prior experience with membrane protein or immunohistochemistry (IHC) analysis is highly desirable.
• Basic knowledge of cell biology, pathology, or histological staining principles is an advantage, particularly in understanding membrane-localized protein expression.
• Ability to rapidly learn new concepts and integrate knowledge across AI, biology, and clinical domains.
• Experience or strong interest in collaborative research with hospitals and clinical partners, including interaction with pathologists and clinicians.
• Strong communication skills, with the ability to present research outcomes clearly at internal meetings, seminars, and external conferences.
• Proven capability in scientific writing, including technical documentation, reports, and peer-reviewed publications.
• Good research practice, including code version control (e.g. Git), experiment tracking, and adherence to reproducible research standards.

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.