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.
As part of its continued growth, Qubit Pharmaceuticals is seeking a Research Scientist to develop and implement machine learning force fields. Your work will directly accelerate molecular dynamics and free energy calculations, supporting current and future drug discovery projects.
The perfect fit for this job
We're seeking a highly innovative Research Scientist to join our team. The ideal candidate has deep, hands-on expertise at the intersection of computational chemistry, physics, and machine learning. You are a problem-solver, capable of both developing novel ML-based potentials and applying them to push the boundaries of molecular simulations, enabling us to tackle complex challenges in drug discovery
Your role
As a member of CC team, you will be responsible for:
- Implement Machine Learning Interaction Potentials into molecular dynamics simulation pipelines, ensuring they are robust, scalable, and optimized for High-Performance Computing (HPC) and GPU-accelerated environments
- Partner closely with computational chemists and medicinal chemists to apply ML-based simulations to key drug discovery problems, such as binding affinity prediction and conformational sampling
- Analyze simulation data generated by our models, providing a mechanistic understanding of molecular behavior and communicating complex results to a broad scientific audience
- Stay up-to-date with the latest advancements in ML-based potentials and related fields, contributing to the scientific strategy and intellectual property of the company
Your qualifications and skills
- Ph.D. in Computational Chemistry, Physics, or a related field with a strong focus on machine learning and molecular modeling
- A minimum of 3 years of post-doctoral or industry experience developing or applying ML-based potentials
- Extensive hands-on experience with deep learning frameworks and a strong understanding of neural network architectures relevant to molecular modeling
- Deep theoretical and practical knowledge of molecular dynamics and classical force fields
- Proficiency in programming, with expertise in Python being essential
- Experience with High-Performance Computing (HPC) environments
- Experience with ML-based potentials and an understanding of their underlying principles
- Familiarity with quantum chemistry (QM) methods and software (e.g., Gaussian, VASP, ORCA) for generating high-quality training data
- Experience with molecular dynamics simulation packages (e.g., Tinker, GROMACS, LAMMPS, OpenMM)
- A track record of scientific publications or contributions to open-source software in the field of ML potentials
The proposal benefits & perks
- Duration: Full time – Permanent
- Starting from January 2026
- Salary according to profile
- Health insurance and provident fund 100% covered
- Lunch vouchers worth €9 covered at 50%.
- Location: Paris 14th arrondissement
- Possibility of remote work for 2 days per week.
