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Molecular Modeling Intern
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Qubit Pharmaceuticals is a French-American deeptech startup, focusing on discovering novel molecules for complex targets in healthcare and materials science. We leverage proprietary molecular simulation and quantum-physics based modeling technology to develop our own discovery programs that we either co-develop with or license out to pharmaceutical and industrial partners. This enables us to design more effective and safer drug candidates, aiming to significantly reduce the time and investment needed for discovery. In just 18 months, Qubit Pharmaceuticals grew its portfolio to 7 programs in oncology, immunology & antivirals.
Our cutting-edge technology is based on over 30 years of research by our academic founders, and relies on three main components: in-depth expertise in computational science and high-performance computing (HPC), quantum chemistry and artificial intelligence algorithms, and a powerful, automated cloud platform for molecular simulation with chemical accuracy. We recently announced the launch of the world's most powerful AI foundation model for molecular simulation.
Qubit Pharmaceuticals is seeking a highly motivated and detail-oriented scientist to join our team as a Molecular Modeling Intern (M/F). This is a cutting-edge opportunity to apply state-of-the-art machine learning foundation models to solve complex, therapeutically relevant biochemical problems.
The perfect fit for this jobWe are looking for a highly curious and technically proficient individual ready to contribute to fundamental research with industrial impact.
The goal of this study is to leverage the proprietary FeNNix-Bio1 foundation machine learning model to conduct in-depth studies of fundamental enzymatic processes.
You will be at the forefront of this effort, utilizing these advanced models to move beyond traditional computational approaches and achieve unprecedented accuracy and efficiency in modeling complex biochemical reactions.
Key Responsibilities
During this 6-month internship, you will:
Employ foundation models for large-scale Molecular Dynamics (MD) simulations and detailed structural analysis
Conduct in-depth analysis of proton transfer mechanisms and the stability of catalytic residues within therapeutically relevant enzymes
Prepare enzyme systems and execute MD simulations
Post-process complex simulation data to derive insights on binding site interactions and fundamental proton transfer mechanisms
Translate computational insights into testable hypotheses for rational enzyme design and optimization
Model and explore suggested engineered enzyme variants using advanced MD-based approaches integrated with the FeNNix-Bio1
- Master 2 or final year of a Master's degree in Computational Chemistry, Molecular Modeling, Bioinformatics, or a closely related field
- Strong theoretical foundation in Molecular Modeling, Molecular Dynamics (MD), Thermodynamic Concepts, and Structural Biology
- Proficiency in Python
- A strong interest in the application of Machine Learning to biological systems and rational protein design
- Duration: 4 to 6 months
- Starting date: from February 2026
- Lunch vouchers worth €9 covered at 50%.
- Location: Paris 14th arrondissement
