We are seeking a highly skilled and motivated Research Officer with expertise in artificial intelligence (AI) and spatial multi-omics to join our dynamic research team. This role will focus on driving advancements in personalized cancer immunotherapy, particularly in the development of personalized cancer vaccines, through the integration of cutting-edge AI methodologies with spatial multi-omics data analysis. The position offers a unique opportunity to address key challenges in immunotherapy, including the discovery of predictive biomarkers and the comprehensive characterization of the tumor microenvironment.

Job description:

We are seeking a highly skilled and motivated Research Officer with expertise in artificial intelligence (AI) and spatial multi-omics to join our dynamic research team. This role will focus on driving advancements in personalized cancer immunotherapy, particularly in the development of personalized cancer vaccines, through the integration of cutting-edge AI methodologies with spatial multi-omics data analysis. The position offers a unique opportunity to address key challenges in immunotherapy, including the discovery of predictive biomarkers and the comprehensive characterization of the tumor microenvironment.

Key Responsibilities:

• Develop and implement tissue-based imaging and bioinformatics tools for robust spatial proteomics analysis, aimed at dissecting the complex tumor microenvironment (TME) and identifying precise spatial biomarkers.
• Design and train AI models for virtual staining to visualize spatial omics patterns and multi-omics biomarkers.
• Collaboration & Reporting: Collaborate with pathologists, immunologists, and AI researchers to ensure robust, clinically relevant model development. Prepare reports, presentations, and manuscripts for publication.
• Maintain up-to-date knowledge of bioinformatics methodologies and stay informed about new technologies and computational tools.

Qualifications:

• Bachelor degree in AI/ML, or a related field with a strong focus on imaging and deep learning.
• Expertise in AI techniques and experience in biomedical image analysis.
• Strong programming skills in Python or R, with experience in deep learning frameworks (e.g., PyTorch, TensorFlow).
• Domain Knowledge: Familiarity with cancer immunology and biomarker development.
• Proven experience in developing and evaluating complex machine learning models, especially for biomarker discovery and clinical applications.
• Excellent interpersonal and communication skills to work effectively within a multidisciplinary team of scientists, clinicians, and technical staff.

Preferred Skills:

• Experience with server-based and high-performance computing environments.
• Experience in computational tool development.
• Expertise in managing and analyzing large datasets from various omics platforms

The above eligibility criteria are not exhaustive. A*STAR may include additional selection criteria based on its prevailing recruitment policies. These policies may be amended from time to time without notice. We regret that only shortlisted candidates will be notified.