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 looking for an Intern (M/F) in Quantum Algorithms for the Calculation of Molecular Property through Energy Derivatives

The perfect fit for this job 

We are looking for a detail-oriented programmer who is willing to develop a new branch of research: quantum computing for excited states and properties derived from energy.

Your role 

This project aims to explore the potential advantages of using quantum algorithms to compute molecular energy gradients. We will investigate whether a fully quantum workflow, from wave-function approximation to derivative calculation, can offer a computational advantage over classical or hybrid quantum-classical approaches, particularly by leveraging techniques that can reduce the number of queries required.

Internship Objectives

The primary goal of this internship is to implement and evaluate a quantum algorithm for computing first-order energy derivatives for a specific molecular property. The project is divided into the following key objectives:

• Literature Review: Conduct a comprehensive review of classical numerical differentiation methods and state-of-the-art quantum algorithms for gradient computation,

• Algorithm Implementation: Implement a quantum circuit pipeline to calculate the first-order derivative of the energy for a simple molecular system. The initial focus will be on the dipole moment, which involves derivatives with respect to an external electric field.

• Application and Analysis: Apply the implemented pipeline to a toy model, such as the H₂ molecule. Evaluate the computational cost, accuracy, and scalability of the method compared to classical finite difference calculations.

• Extension: If initial objectives are met, the project can be extended to the calculation of nuclear forces for geometry optimization.

Your qualifications and skills

• Master 2 or final year of engineering school with curriculum specialized in at least one of these topics: quantum chemistry, molecular science (with a solid background in computational science), applied mathematics or quantum computing (for quantum computing: need for a genuine interest in quantum chemistry applications).

Common requirements for all candidates include:

• Good programming skills, preferably in Python and/or Julia.

• Knowledge of standard quantum chemistry methods and/or quantum algorithms for quantum chemistry,

• A strong motivation to work at the intersection of chemistry, physics, and computer science.

The proposal benefits & perks

• Duration: 6 months
• Starting date: from February 2026
• Lunch vouchers worth €9 covered at 50%.
• Location: Paris 14th arrondissement