Research Fellow

The Lee Kong Chian School of Medicine (LKCMedicine) trains doctors who put patients at the centre of their exemplary care. The School, which offers both undergraduate and graduate programmes, is named after local philanthropist Tan Sri Dato Lee Kong Chian. Established in 2010 by Nanyang Technological University, Singapore, in partnership with Imperial College London, LKCMedicine aims to be a model for innovative medical education and a centre for transformative research. The School's primary clinical partner is the National Healthcare Group, a leader in public healthcare recognised for the quality of its medical expertise, facilities and teaching. The School is transitioning to an NTU medical school ahead of the 2028 successful conclusion of the NTU-Imperial partnership to set up a Joint Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in healthcare, with an expanded scope in the medical humanities. Graduates from the five-year undergraduate medical degree programme will have a strong understanding of the scientific basis of medicine, with an emphasis on technology, data science and the humanities.We are seeking Research Fellow to join the Neuroscience and AI Research (Nair) group, led by Nanyang Assistant Professor Aditya Nair, to study how machine learning models and neural circuits in the brain process states of emotion. The Nair group combines cutting-edge systems neuroscience tools with the development of new AI methods to understand and model complex brain data. The ideal applicant will have expertise in either systems neuroscience or NeuroAI/machine learning, particularly in analysis of large-scale neural data. The group places a strong emphasis on mentorship and nurturing talent, and the applicant can expect to engage in highly collaborative research.Key Responsibilities: For systems neuroscience focus: Perform in-vivo neural recordings in rodent models of social behavior and decision making. For NeuroAI focus: Analyze high-dimensional brain data, document results and carry out an independent research project. For NeuroAI focus: Develop and apply new machine learning and computer vision methods such as large-language models and vision-language models for high-throughput analysis of video data. For NeuroAI focus: Apply data-driven dynamical system modeling tools using specialized software packages to elucidate neural computations involved in emotion. Prepare and contribute to grant applications and conference presentations. The candidate is also expected to write and draft research publications in top neuroscience and AI journals. Attend a weekly lab meeting and journal club and present data and/or papers as necessary. Key Competencies and Requirements: Doctoral degree (PhD) in systems neuroscience or computational neuroscience/AI/ML or relevant fields. We also invite candidates with interdisciplinary backgrounds to apply. For systems neuroscience focus: Experience with stereotaxic surgery in rodents, optogenetics and in-vivo microendoscopic imaging. For systems neuroscience focus: Experience with large-scale electrophysiology recordings with silicon probes or Neuropixel probes is highly advantageous. For NeuroAI focus: Strong programming skills in Python and Matlab. For NeuroAI focus: Familiarity with analyzing large-scale neural data (such as imaging datasets, electrophysiology datasets or video data) is highly desirable. For NeuroAI focus: Proficiency in popular deep learning, computer vision and/or user-interface software frameworks (such as Pytorch, TensorFlow, OpenCV, PyQt, Gradio etc). The candidate is expected is have a strong numeric and analytical background. Competent in information visualization. A working knowledge of Adobe Illustrator is a strong advantage. Ability to work independently and collaboratively in a multidisciplinary environment. Entry level candidates are welcome to apply We regret to inform that only shortlisted candidates will be notified.