Principal Computational Chemist

About Aqemia

Aqemia is a next-generation pharmatech reinventing drug discovery with quantum-inspired physics and generative AI.

Our mission: design innovative small-molecule drug candidates for dozens of critical diseases, faster and smarter, without relying on experimental data.

Unlike traditional approaches, Aqemia starts drug discovery purely in silico. By combining physics-based models with large language models trained on proprietary data, we identify promising molecules with high accuracy before synthesis.

We’ve already delivered multiple preclinical successes and secured strategic partnership. Our internal pipeline is growing fast, with several programs in in vivo optimization.

We’re a team of 65+ based in Paris and London, we bring together chemists, physicists, engineers, and machine learning experts to push the boundaries of what’s possible in early-stage drug discovery.

As Principal Computational Chemist, you'll lead the development of cutting-edge computational chemistry pipelines within Aq’s Drug Discovery Platform. Collaborating with computational chemists, AI researchers, and drug discovery experts, you'll integrate innovations to accelerate novel therapeutic discovery.

We are seeking a Principal Computational Chemist, the most senior individual contributor rank s role is designed for a scientist at the state of the art of their field, with deep expertise and a strong track record of impactful contributions. The Principal Computational Chemist will oversee complex scientific projects, mentor scientists, and actively shape our scientific roadmap.

• Be a Technical Leader - Drive the development of cutting-edge computational chemistry methodologies for molecular modeling and drug discovery.
• Mentor and Support the Team - Act as a scientific and technical mentor to junior and mid-level researchers, fostering innovation and knowledge-sharing within the team.
• Bridge Research and Application - Work closely with interdisciplinary teams (computational chemistry, AI and drug discovery experts) to translate computational chemistry research into real-world impact.

• Lead research initiatives to develop and apply novel computational chemistry methods to virtual screening, hit optimisation and lead optimisation.
• Design and implement advanced computational chemistry techniques
  , including protein ligand complex generation.
• Collaborate with interdisciplinary teams
  , including computational chemists, AI Research scientists, physicists, data scientists and medicinal chemists.
• Mentor and guide junior researchers and engineers
  , fostering a culture of scientific innovation and excellence.

Polite note: this position does not involve manual compound design in Drug Discovery Programs.

• PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or a related field.
• Extensive experience (10+ years) in computational chemistry and drug discovery including 5 years in the drug discovery industry.
• Recognised expertise in molecular modeling, complex generation, protein-ligand interactions, free energy calculations, virtual screening, ADME properties and related areas.
• Strong knowledge of uncertainty quantification and its application in molecular design.
• Proven ability to deliver impactful scientific contributions at the forefront of the field.
• Experience mentoring and guiding scientists in a collaborative, high-performance environment.
• Proficiency in programming (e.g., Python) and experience with industry-standard computational chemistry tools.
• Strong problem-solving skills, autonomy and a collaborative mindset.

• Pragmatic and Impact-Driven - Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability.
• Eagerness to Learn - A strong curiosity for scientific advancements and a willingness to continuously expand your expertise.
• Love for High Scientific Challenges - Enthusiasm for tackling complex problems at the frontier of AI and drug discovery.
• Team-Oriented - A collaborative spirit, thriving in an interdisciplinary environment.
• Humility - Open to feedback and different…