Deskripsi Pekerjaan
Are you a visionary Scientist or Senior Scientist passionate about revolutionizing healthcare through cutting-edge technology? The Agency for Science, Technology and Research (A*STAR)'s Biomedical Institute (BII) invites you to join our dynamic Precision Health team in vibrant Singapore. We are actively seeking a highly motivated and innovative individual to lead the development and application of advanced agentic AI methodologies for sophisticated multi-omics data analysis. This pivotal role offers an unparalleled opportunity to accelerate groundbreaking biomedical discoveries, unravel complex disease mechanisms with unprecedented detail, and translate profound research insights into tangible, life-changing improvements in patient outcomes globally.
As a key member of our team, you will be at the forefront of integrating vast and diverse biological datasets – spanning genomics, transcriptomics, proteomics, and metabolomics – to construct robust predictive models and forge innovative solutions for personalized medicine. You will leverage the power of artificial intelligence to identify novel biomarkers, predict disease progression, and optimize therapeutic strategies, thereby contributing directly to the advancement of precision healthcare. We foster an intellectually stimulating and collaborative, interdisciplinary environment where creativity and scientific rigor are highly valued. If you possess a strong drive to make a profound and lasting impact on global health, thrive on tackling complex scientific challenges, and are eager to contribute to a world-class research institution, we strongly encourage you to apply. This is more than just a research position; it's a strategic chance to fundamentally shape the future of precision healthcare in one of Asia's leading scientific hubs.
Tanggung Jawab
- Lead the research, design, and implementation of agentic AI algorithms for the integration and analysis of multi-omics datasets (e.g., genomics, transcriptomics, proteomics, metabolomics).
- Develop novel computational strategies and bioinformatics pipelines to extract actionable insights and identify significant patterns from large-scale biological data.
- Collaborate effectively with biologists, clinicians, data scientists, and engineers to define research questions, design experiments, and interpret complex data.
- Contribute significantly to grant proposals, publish research findings in high-impact scientific journals, and present at international conferences and symposia.
- Mentor junior scientists and research assistants, fostering a culture of innovation, scientific rigor, and continuous learning within the team.
- Translate research discoveries into potential diagnostic tools, therapeutic targets, or personalized treatment strategies for real-world application.
- Evaluate, adapt, and implement state-of-the-art machine learning and deep learning techniques relevant to precision health and biomedical research.
Kualifikasi
- PhD in Bioinformatics, Computational Biology, Computer Science, Data Science, Artificial Intelligence, or a closely related quantitative field.
- Proven track record (minimum 2+ years post-PhD for Scientist; 5+ years post-PhD for Senior Scientist) in developing and applying AI/ML models, specifically for biological or medical data.
- Strong expertise in multi-omics data analysis and integration (e.g., genomics, transcriptomics, proteomics, metabolomics).
- Proficiency in programming languages such as Python or R, with hands-on experience in relevant libraries (e.g., TensorFlow, PyTorch, scikit-learn).
- Demonstrated ability to publish in peer-reviewed journals and present complex research findings effectively to diverse audiences.
- Excellent problem-solving skills, critical thinking, and the ability to work independently and collaboratively in a fast-paced, interdisciplinary research environment.
- Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and high-performance computing (HPC) environments is highly advantageous.
- Strong communication and interpersonal skills to engage effectively with scientific, clinical, and technical teams.