Computational Scientist

About us AL/ML and data science is an important component of biomedical and translational research, where data of multiple modalities are being constantly generated at an unprecedented scale. The Research Data Integration group in the Bioinformatics Institute (BII), A*STAR, aims to bridge the complexity of computational biology and data science with the hypotheses and findings of biologists and clinicians. One of our immediate challenges is to analyze, integrate and analyze multi omics, imaging and clinical data generated by biomedical institutes in A*STAR, healthcare institutions and national initiatives in Singapore in the areas of cancer, metabolic, eye and skin diseases. We seek motivated individuals to join us to push the potential of biomedical data in driving biological discoveries and create translational impact that benefits patients. Position summary We are seeking a highly motivated Computational Scientist with expertise in artificial intelligence, multi omics data integration, and metabolic disease biology. The successful candidate will play a critical role in developing AI/ML frameworks to integrate and analyze high dimensional biological datasets (e.g., genomics, transcriptomics, proteomics, imaging) with clinical data to identify novel mechanisms, biomarkers, and therapeutic targets in metabolic diseases such as MASLD/MASH and obesity. This position offer the candidate an opportunity to work closely with a diverse and collaborative team of computational and experimental scientists, and clinicians on cutting edge research at the intersection of AI and human health, and drive translational impact in metabolic diseases. Key Responsibilities Develop and implement AI/ML models to analyze and integrate multi omics and clinical datasets related to metabolic disorders. Collaborate with biologists and clinicians to generate testable hypotheses from integrated datasets, and contribute actively to laboratory validations and screening studies through analytical findings. Design pipelines for preprocessing, normalization, and harmonization of heterogeneous data types. Apply and develop novel computational methodologies to uncover disease mechanisms. Drive biomarker discovery, patient stratification, target identification using machine learning approaches. Build a database integrating and linking multi dimensional clinical and multi omics data for metabolic diseases. Develop visualizations and dashboards to communicate complex data insights to interdisciplinary teams. Stay up to date with emerging computational techniques and tools in systems biology and AI. Drive high impact scientific publications, patent filings, presentations and grant proposals. Qualifications Ph.D. in Computational Biology, Bioinformatics, Computer Science, Data Science, Systems Biology, or a related field. Strong background in programming and AI/ML (e.g., deep learning, ensemble methods, graph based learning, agentic AI, explainable AI). Proficiency in programming languages such as Python and R; experience with AI/ML frameworks like TensorFlow, PyTorch, or scikit learn. Demonstrated experience in integrating and analysing complex multi omics datasets (e.g., RNA seq, WGS, proteomics, GWAS). Highly experienced with Unix/Linux environment and/or cloud architecture. Solid understanding of metabolic disease biology and relevant clinical phenotypes. Experience working with large scale multi dimensional datasets from biobanks, cohorts, or clinical trials. Track record of peer reviewed publications in computational biology or bioinformatics. Experience in a cross functional, collaborative environment in academia or industry. Knowledge in data security, data standards and interoperability, and reproducible research practices. Strong analytical and problem solving skills, and attention to details. Excellent oral and written communication and presentation skills. Able to work independently and work collaboratively in a multi disciplinary team environment. Competent project and data management, and organizational skills. 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. #J-18808-Ljbffr