Research Fellow (Artificial Intelligence for Life Sciences Applications)
Research Fellow (Artificial Intelligence for Life Sciences Applications)
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Job Description
The School of Materials Science and Engineering (MSE) at NTU is seeking a Research Fellow in Artificial Intelligence for Life Sciences Applications. The successful candidate will lead research that applies AI to tackle challenges in aquaculture and drug delivery working at the interface of materials science biology and computational modeling.
Key Responsibilities:
Lead and execute AI-driven research projects in aquaculture (e.g. health monitoring yield prediction system optimization) and/or drug delivery (e.g. predictive modeling nanocarrier design therapeutic response analysis).
Develop train and validate advanced computational models and machine learning algorithms tailored to complex datasets.
Collaborate with multidisciplinary teams including biologists engineers and clinicians 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 Biomedical Engineering or a related discipline.
Strong research expertise in machine learning deep learning or computational modeling with demonstrated application in life sciences aquaculture or drug delivery.
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 clinical data).
Proficiency in programming languages such as Python R or MATLAB and familiarity with machine learning frameworks (e.g. TensorFlow PyTorch Scikit-learn).
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: NTUEmployment Type
Full-Time
