Job Description
Join NTU's Precision Medicine Revolution in AI-Powered IVF
Nanyang Technological University's Lee Kong Chian School of Medicine (LKCMedicine) is seeking a highly motivated Research Assistant/Associate to join our cutting-edge precision medicine research team. This is a unique opportunity to contribute to transformative AI-driven solutions for IVF outcome prediction, leveraging state-of-the-art machine learning and large-scale clinical datasets. You will work at the intersection of reproductive medicine, data science, and artificial intelligence, helping to improve fertility treatment success rates and patient outcomes. As part of a multidisciplinary team of clinicians, bioinformaticians, and AI experts, you will design and implement predictive models, analyse complex biomedical data, and publish high-impact research. The role offers exposure to real-world clinical data, collaboration with leading fertility specialists, and the chance to shape the future of reproductive healthcare. If you are passionate about applying AI to solve critical medical challenges, this position provides an ideal platform for career growth in academic research or the biotech industry.
Responsibilities
- Develop and validate machine learning models for predicting IVF outcomes using clinical and genomic data.
- Preprocess, clean, and manage large-scale datasets from electronic health records and fertility clinics.
- Collaborate with clinicians to define research questions and translate clinical needs into analytical pipelines.
- Design and conduct statistical analyses to identify biomarkers and prognostic factors.
- Write scientific manuscripts, prepare reports, and present findings at conferences and meetings.
- Maintain documentation of methodologies, code, and results for reproducibility.
- Contribute to grant applications and research proposals.
- Mentor junior team members and assist in lab management tasks.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Biomedical Engineering, Statistics, or a related field.
- Strong programming skills in Python or R; experience with machine learning libraries (scikit-learn, TensorFlow, PyTorch).
- Familiarity with reproductive biology or clinical IVF data is a strong plus.
- Proven ability to work with large, complex datasets (e.g., EHRs, omics data).
- Excellent written and verbal communication skills in English.
- Track record of publications in peer-reviewed journals (preferred for Associate level).
- Ability to work independently and collaboratively in a fast-paced research environment.
- Prior experience in precision medicine or AI in healthcare is advantageous.