Paid Research Assistant — AI in Medical Imaging

A2 Innovation Lab; On; Sur place; EUR 2 000 - 3 000; Plein temps

Avantages offerts par ce poste

Mentorship from experiencedResearchers

Opportunity to work on cutting-edge AI

Skill development through close指导

Résumé du poste

TOGAI Lab (Transforming Global Health with AI) at NAAMII invites fresh graduates or applicants with research experience to work in Kathmandu on medical image analysis using AI. You will learn directly from the Research Director Bishesh Khanal, tackling problems in low-resource settings and applying state-of-the-art methods to real-world health data.

You will contribute to disease diagnosis, medical image segmentation and vision-language tasks, with opportunities to publish and grow through

Qualifications

• Currently 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

Responsabilités

• Apply and co-develop methods for medical image analysis
• Implement state-of-the-art machine learning methods
• Evaluate performance and critically assess the literature
• Work directly with Research Director Bishesh Khanal, learning and applying AI in low-resource settings

Connaissances

Machine Learning foundations

Python programming

PyTorch

Scikit-learn

Communication & teamwork

Formation

Bachelors in Computer Science / Engineering

Outils

PyTorch

Scikit-learn

Description du poste

TOGAI Lab (Transforming Global Health with AI) at NAAMII invites fresh graduates or applicants with research experience to work in Kathmandu on medical image analysis using AI. You will learn directly from the Research Director Bishesh Khanal, tackling problems in low-resource settings and applying state-of-the-art methods to real-world health data.

You will contribute to disease diagnosis, medical image segmentation and vision-language tasks, with opportunities to publish and grow through