Senior Applied Scientist - Genomics AI

Key Skills

Aartificial intelligence, Deep Learning, Genomic data, Large Language Models - LLMs, Machine learning techniques, Python Programming, US Healthcare Recruitment

Job Description

With operations in 27 countries across 4 continents, M42 is at the epicenter of AI innovation in healthcare, driving the Emirati Genome Program, the world's largest population genome program. As part of a cross-functional and internationaly-trained team, you'll be working on cutting-edge AI projects that have a significant impact on global healthcare.

As a Senior Applied Scientist at M42, you will have the exciting opportunity to work on building AI systems powered by foundation models in healthcare. You will work alongside world-class peers in driving forward projects that build foundational models for Genomics, Language, Imaging, EHR, and Multimodal AI.

Responsibilities

Core Responsibilities:

• Lead the ideation, creation, and refinement of foundational AI models for healthcare data including text (LLM), genomics, EHR, and imaging, among others.
• Collaborate with cross-disciplinary teams to translate genomic data into actionable insights.
• Foster interdisciplinary collaboration for the seamless integration of these models into products.
• Play a significant role in shaping our strategic AI roadmap.
• Stay at the forefront of AI in healthcare advancements.
• Mentor junior colleagues in the team. Teach and learn from your colleagues.

Qualifications

Key Qualifications:

• PhD or MS in AI, Computer Science, or related field.
• 2+ years of work experience (5+ with MS) in industry or as a postdoc.
• Experience with foundation models and transformer architectures.
• Proficient in machine learning and deep learning.
• Strong programming skills in Python and familiarity with ML frameworks.
• Outstanding problem-solving abilities, critical thinking skills, and team-player spirit.
• A strong interest in learning and growing – we work in a fast-evolving field.

What to Expect

Work Environment:

• Challenging healthcare AI problems, involving some of the largest datasets in the world.
• Accomplished colleagues who are highly collaborative and collegial.
• Fairly flat hierarchy (merit of ideas over rank) with high ownership for solving problems.

Career Growth:

• Opportunities for career progression.
• Regular learning and development opportunities as a team (weekly reading/discussion groups and more) to help you grow in healthcare AI.