Research Fellow (Artificial Intelligence for Life Sciences Applications) Full-time

Research Fellow In Artificial Intelligence For Aquaculture Applications

The School of Materials Science and Engineering (MSE) at NTU is seeking a Research Fellow in Artificial Intelligence for Aquaculture Applications. The successful candidate will lead research that applies AI to tackle challenges in aquaculture and drug delivery, interface of materials science, biology, and computational modeling.

Key Responsibilities:

• Lead and execute AI-driven research projects in aquaculture (e.g., behavioral analysis, growth prediction, digital twin, computer vision.)
• Develop, train, and validate advanced computational models and machine learning algorithms tailored to complex datasets.
• Collaborate with multidisciplinary teams including biologists, engineers, to translate AI methods into practical solutions.
• Publish high-quality research outcomes in top-tier journals and present findings at international conferences.
• Contribute to grant applications and proposals to secure external funding.
• Mentor graduate students and junior researchers in computational and AI-related research methodologies.
• Maintain and manage computational resources, datasets, and research documentation to ensure reproducibility and integrity.
• Support collaborations with external academic, industry, and government partners to promote translational impact.

Job Requirements:

• PhD in Computer Science, Artificial Intelligence, Data Science, Computational Biology, or a related discipline.
• Strong research expertise in machine learning, deep learning, or computational modeling with demonstrated application in life sciences, aquaculture.
• Proven track record of high-quality publications in relevant international journals or conferences.
• Experience handling complex, multi-modal datasets (e.g., biological, imaging, environmental, or data).
• Proficiency in programming languages such as Python and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and image segmentation model (e.g. YOLO-seg, SAM)
• Ability to work independently and collaboratively in a multidisciplinary environment.
• Strong analytical, problem-solving, and communication skills.
• Prior experience in grant writing, project management, or mentoring students is advantageous.

We regret to inform that only shortlisted candidates will be notified.

Hiring Institution: NTU