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Job Description
The National University of Singapore invites applications for Research Assistant/ Research Associate in the Department of Clinical Imaging Research Centre (CIRC) Yong Loo Lin School of Medicine. CIRC is a dedicated molecular imaging research centre. It is equipped with on-site capability for the preparation of diagnostic and therapeutic radiopharmaceuticals in a modern GMP-certified facility. CIRC is positioned to support both academic and commercially led clinical research programs, with dedicated clinical imaging facilities area advanced modalities of PET-CT and PET-MRI. For more details on what we do, do visit https://medicine.nus.edu.sg/circ/. Appointments will be made on a two-years contract basis with the possibility of extension.
Purpose of the post
We are seeking a highly skilled and innovative Research Assistant/Research Associate with specialisation in Medical Image Analytics to join our team to usher in the next era of automated analysis of multi-modal biomedical images by integrating image processing /computer vision technologies into bio-imaging problems.
The successful candidate will join Image/signal processing team and be involved in the team's role of supporting the research performed at the Clinical Imaging Research Centre, NUS, Singapore. The work involves design, analysis, implementation, integration and visualization of a wide range of low to high level biomedical image-processing activities for MR, CT, PET, Optical modalities. In addition, this position will have a strong focus on multi-modal image analysis, registration, segmentation, dynamic modelling and visualization. The candidate will be expected to have proficiency in image registration, visualization of bio-imaging data, and have a strong background in data analytics, artificial intelligence, and statistical analysis, coupled with proficient programming skills.
Main Duties and Responsibilities
The Research Assistant/ Research Associate will be able to perform the following:
- Algorithm Development: Design and develop advanced AI and machine learning algorithms for medical image analysis, including image segmentation, registration, and classification.
- Data Analytics: Apply data analytics techniques to process and analyse large volumes of medical imaging data, extracting meaningful insights to support clinical decision-making.
- Statistical Analysis: Conduct rigorous statistical analyses to validate and interpret the results of image analytics, ensuring robustness and reliability.
- Software Development: Develop and maintain software tools and pipelines for the automated processing and analysis of medical images.
- Collaborative Research: Work closely with cross-functional teams, including radiologists, clinicians, and researchers, to understand requirements, gather feedback, and refine analytical methods.
- Technical Documentation: Document algorithms, processes, and results in a clear and concise manner, facilitating knowledge transfer and reproducibility.
- Stay Current: Keep abreast of the latest developments in medical imaging, AI, and data analytics, incorporating new techniques and methodologies into existing workflows.
Qualifications
- Education: Master’s or bachelor’s degree in computer science, Biomedical Engineering, Electrical Engineering, Data Science, or a related field.
- Experience: 1+ years of experience in medical image analysis, data analytics, and AI.Demonstrated experience with image processing techniques and tools (e.g., ITK, VTK, OpenCV).
Implementation of various deep learning models.
Proficiency in statistical analysis and statistical software (e.g., R, SAS, MATLAB).
- Technical Skills:Strong programming skills in languages such as Python, R and MATLAB.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn).
Excellent problem-solving abilities and a strong analytical mindset, with the ability to interpret complex data and generate actionable insights.
Effective communication skills, both written and verbal, with the ability to present technical information to a non-technical audience.
Ability to work collaboratively in a multidisciplinary team environment, managing multiple projects simultaneously.
Preferred Qualifications
- Experience in deep learning techniques for medical image analysis (e.g., convolutional neural networks, UNets, Transformers, GANs).
Knowledge of medical imaging modalities (e.g., MRI, CT, PET) and DICOM standards.
Background in healthcare and clinical applications of medical imaging.
Remuneration will be commensurate with the candidate’s qualifications and experience.
Formal application: Please submit your application, indicating current/expected salary, supported by a detailed CV (including personal particulars, academic and employment history, complete list of publications/oral presentations and full contacts of three (3) referees to this job portal.
We regret that only shortlisted candidates will be notified.
