Position: Research Assistant (Paid Position), Full time
Application Deadline: On a rolling basis till April 30th, 2025
Categories: Vacancies
TOGAI Lab (Transforming Global Health with AI) at NAAMII is seeking highly motivated fresh pass-out students or applicants with some research experience to work at TOGAI Lab in Kathmandu. As part of the lab, you will work directly with our Research Director Bishesh Khanal, learning and applying AI in low-resource settings and tackling problems specific to countries like Nepal.
TOGAI Lab has a track record of cutting-edge research on topics such as Disease Diagnosis, Medical Image Segmentation, Vision-Language Models, with high-quality publications at top-tier conferences and journals. This opportunity offers a chance to apply and co-develop methods for medical image analysis, implement state-of-the-art machine learning methods, evaluate their performance, and critically assess the literature.
Eligibility Criteria:
- Completed (or awaiting Thesis Defense) final year in Undergraduate degree in Computer Science / Engineering, or related fields
- Strong foundational knowledge in Machine Learning and its mathematics (Probability & Statistics, Calculus, Linear Algebra)
- Familiarity with programming languages such as Python, and frameworks like PyTorch, Scikit
- Keen interest in research and self-motivated
- Good communication and teamwork abilities
Preferred Qualifications:
- Good low-level understanding and algorithmic details of technical topics you have worked on
- Track record in implementing algorithms beyond calling library APIs, with clean code practices and testing
- Prior experience in projects related to Computer Vision or Medical Imaging is a plus
Benefits:
- Opportunity to work on cutting-edge research projects and produce high-quality publishable work
- Mentorship from experienced researchers and industry professionals
- Skill development through close mentorship and supervision
How to Apply:
Apply online via the tangible.careers platform by April 30, 2025. Shortlisted participants will be notified via the platform by May 1st Week.
Note: Upload evidence examples to demonstrate your understanding of fundamentals. These examples do not have to match exactly but should justify your competency for the given rubric.
Fresh pass-outs or students completing their final semester with a good foundation in Linear Algebra, Machine Learning algorithms, and frameworks/tools are strongly encouraged to apply. Commitment to self-motivated learning is required.
For more information, contact: [email protected]
NAAMII encourages applications from diverse backgrounds and perspectives.