"Research Fellow (Cancer Science Institute, Prof Yang Zhang's Lab)"

Posting Start Date: 19/12/2025

Job Description

To provide dedicated scientific and technical support for the development of advanced AI methods and foundation models in computational biology, ensuring the timely execution of funded research projects and the achievement of the laboratory’s research objectives in alignment with the University’s mission in scientific excellence and innovation.

Duties & Responsibilities

• Conduct independent and collaborative research on AI-driven modeling of proteins, RNAs, and biomolecular interactions, contributing to high-impact publications and grant deliverables.
• Design, implement, and optimize advanced machine learning and deep learning algorithms for computational biology and biomedical applications.
• Support the execution of funded research projects by meeting technical milestones, maintaining research quality, and ensuring timely progress.
• Collaborate with PI, postdoctoral fellows, and students to integrate methods across projects and provide technical guidance where appropriate.
• Assist in mentoring junior researchers and contribute to the preparation of manuscripts, reports, and grant-related documentation.

Qualifications

• Qualification: Ph.D. in Computer Science, Information Science, Artificial Intelligence, Computational Biology, or a closely related quantitative discipline.
• Experience: Proven research experience at the doctoral or postdoctoral level, with a strong publication record in peer-reviewed journals and/or top-tier conferences.
• Knowledge & Skills:
  • Strong foundation in machine learning, deep learning, and algorithm development.
  • Proficiency in scientific programming (e.g., Python, PyTorch/TensorFlow, C/C++ as appropriate) and experience with large-scale data analysis.
  • Demonstrated ability to develop novel AI methods and adapt them to complex scientific problems.
  • Ability to work independently as well as collaboratively in a multidisciplinary research environment.
  • Excellent written and verbal communication skills for scientific publications and presentations.

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