Computational ADMET Scientist - Drug Metabolism / Metabolomics Focus - Remote

Overview

Deep Origin is a biotechnology company accelerating drug discovery through AI-powered tools. Our platforms simplify R&D, simulate biology, and empower scientists to solve diseases and extend human healthspan through software solutions and partnerships. We combine cutting-edge computational science with deep biological expertise to tackle some of the most pressing challenges in healthcare.

In Short

• Seeking a Computational ADMET Scientist with expertise in drug metabolism.
• Design and build predictive systems for Phase I and Phase II metabolic pathways.
• Contribute to the development of AI-driven tools for drug design.
• Focus on predicting metabolic routes and enzyme involvement.
• Analyze regioselectivity and metabolite toxicity.
• Work at the intersection of data mining and computational science.
• Utilize statistical and kinetic modeling techniques.
• Incorporate cheminformatics and machine learning in research.
• Collaborate with scientists to solve healthcare challenges.
• Position based in the United States.

Requirements

• Deep expertise in drug metabolism.
• Experience in predictive modeling and cheminformatics.
• Strong background in machine learning and computational chemistry.
• Ability to work creatively in a scientific environment.
• Familiarity with statistical and kinetic modeling.
• Ability to communicate complex ideas effectively.
• Experience with data mining techniques.
• Strong analytical skills.
• Team player with collaborative spirit.
• PhD or equivalent experience in a relevant field.

Benefits

• Opportunity to work at the forefront of drug discovery.
• Collaborative and innovative work environment.
• Access to cutting-edge technology and tools.
• Potential for professional growth and development.
• Contribute to impactful healthcare solutions.
• Competitive salary and benefits package.
• Work with a team of dedicated professionals.
• Flexible work arrangements.
• Support for continuous learning and education.
• Engagement in meaningful scientific research.