Senior Application Scientist

Aqemia; Greater London; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A forward-thinking pharmatech company in the UK is seeking a Senior Application Scientist to lead molecular simulations projects. You will design large-scale studies, mentor junior scientists, and integrate simulations with experimental insights. A successful candidate will have an MSc or PhD in a related field and 5+ years of relevant experience. The role emphasizes collaboration and innovation, making a significant impact on drug discovery processes. This position offers hybrid work flexibility with a vibrant team culture.

Benefits

Flexible work arrangements

Professional development opportunities

Relocation support and French lessons if needed

Qualifications

• 5+ years of experience in molecular simulations, ideally within a drug discovery context.
• Deep knowledge of free energy methods and molecular dynamics.
• Demonstrated ability to lead scientific projects and communicate effectively.

Responsibilities

• Design and lead large-scale simulation studies for binding free energy predictions.
• Evaluate and improve modeling protocols for reproducibility and efficiency.
• Mentor junior scientists in simulation best practices.

Skills

Molecular simulations

Computational Chemistry

Programming/Scripting

Workflow automation

Education

MSc or PhD in Computational Chemistry or related discipline

Tools

Simulation software

Job description

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About AQEMIA

AQEMIA is a next-gen pharmatech company generating one of the world's fastest-growing drug discovery pipeline.

Our mission is to design fast innovative drug candidates for dozens of critical diseases, such as immuno-oncology.

Our unique approach leverages quantum-inspired physics algorithms to power generative AI in designing novel drug candidates-without relying on experimental data.

We already delivered several drug discovery successes within our internal pipeline and through collaborations with pharmaceutical companies. Our most advanced programs are currently in vivo optimization.

About the Team

The mission of the Molecular Simulations Team is threefold:

• Support drug discovery programs by maximizing the impact of binding free energy calculations in decision-making.
• Build, benchmark and continuously improve reproducible and scalable pipelines for binding free energy calculations, enabling support for multiple programs in parallel.
• Collaborate closely with our Physics Research Team to integrate innovations from Aqemia's proprietary binding free energy methods.

Role Overview

As a Senior Application Scientist in the Molecular Simulations Team, you will be a scientific leader and technical expert, contributing to the strategy and delivery of Aqemia's Binding Free Energy Technology. You will help define and evolve how physics-based simulations inform and accelerate drug discovery decisions at Aqemia.

Key Responsibilities

• Design and lead large-scale simulation studies (e.g., relative and absolute binding free energy predictions).
• Evaluate and improve modeling protocols for reproducibility, accuracy, and efficiency.
• Serve as a mentor to junior scientists, promoting best practices in simulation and analysis.
• Contribute to cross-functional planning and the integration of simulations with experimental and AI-based insights.
• Stay at the forefront of developments in molecular simulations and suggest innovations to the team.
• Support the development and scaling of workflows that can serve multiple drug discovery projects.
• Work closely with the Research Team to implement improvements and updates to Aqemia's proprietary binding free energy methods.

Qualifications & Experience

• MSc or PhD in Computational Chemistry, Biophysics, Statistical Mechanics, or related discipline.
• 5+ years of experience in molecular simulations, ideally within a drug discovery context.
• Deep knowledge of free energy methods, molecular dynamics, and simulation software.
• Strong programming/scripting ability and experience with workflow automation.
• Demonstrated ability to lead scientific projects and communicate effectively across disciplines.

Nice-to-Have

• Experience in machine learning applications for physics-based modeling.
• Track record of scientific publications and contributions to the computational drug discovery community.

Preferred Mindset

• Scientific Rigour: Champion high scientific standards and promote best practices across the team.
• Humble and Willing to Learn: Lead by example with curiosity and openness to new ideas.
• Excited by Challenging Scientific Problems: Passionate about solving complex, cutting-edge problems and guiding others through them.
• Pragmatic and Impact-Driven: Combine strategic thinking with practical execution to deliver real-world impact in a fast-paced environment.
• Leadership through Influence: Inspire and mentor colleagues while fostering a collaborative, high-performance culture.

Why Join Us?

At AQEMIA, we work for a mission: joining us means having your own impact on changing the way drugs are discovered, and helping to shape the direction of our fast-growing company and team.

Expanding Drug Discovery Pipeline

Focused on critical therapeutic areas like Oncology, CNS, Immuno-inflammation... with in vivo proof of concept/patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.

Interdisciplinary Team

Brilliant talent from tech and life sciences.

DeepTech Recognition

Part of French Tech 120 and France 2030.

Prime Location

Based in central Paris and London (King's Cross) with the possibility of 2 remote days per week.

International Environment

The work language is English - relocation support and French lessons granted if needed.

Strong Financial Backing

$100M raised from leading European and International investors

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.