Applied AI Scientist, Aqemia

Salary not provided

Python

Tensorflow

Scikit-Learn

PyTorch

Mid and Senior level

Paris

More information about location

3 days a week in office (Central Paris)

AI and quantum physics driven drug discovery

Posted today

AI and quantum physics driven drug discovery

21-100 employees

B2BArtificial IntelligenceDeep TechMedTech

Posted today

Salary not provided

Python

Tensorflow

Scikit-Learn

PyTorch

Mid and Senior level

Paris

More information about location

3 days a week in office (Central Paris)

21-100 employees

B2BArtificial IntelligenceDeep TechMedTech

Company mission

To design fast innovative drug candidates for dozens of critical diseases, such as immuno-oncology.

Job

Company

Role

Who you are

Strong problem-solving skills, autonomy and a collaborative mindset
MSc or PhD in Computer Science, Machine Learning, Computational Chemistry, or related field
Around 3 years of experience applying ML in scientific or industrial settings
Strong experience with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
Solid Python programming skills and experience working with scientific computing libraries

What the job involves

We are looking for an Applied AI Scientist to join Aqemia’s Drug Discovery Platform as an Applied AI Scientist, working at the intersection of ML and molecular science
50% Applied AI: Contribute directly to internal and partnered drug discovery programs by applying ML rigorously and efficiently in collaboration with chemists and project teams
Own ML workstreams: define goals, manage timelines, communicate with stakeholders
Process molecular datasets and apply robust ML models (QSAR, regression, ranking)
Collaborate with chemists and project leads; deliver results that drive compound prioritisation
Make your models and predictions easily accessible to end users ensuring practical usability in drug discovery workflows
50% AI Research: Develop cutting-edge ML models (e.g. , GNNs, generative models, physics-informed AI) to predict molecular properties and protein-ligand interactions
Design and implement novel ML algorithms (DL, GNNs, generative, physics-based models)
Take part in cutting-edge research and bibliographic exploration
Collaborate with research and drug discovery teams to translate models into actionable insights

Our take

The billion dollar drug discovery industry is set to see notable growth by 2032 with huge R&D investments being made. It’s generally accepted that this is one of the most important financed sectors in the world. AQEMIA joined the discovery train in 2019 with its deep physics and AI enabled drug revelation pipeline.

The company boasts its intricate level of accuracy within its physics algorithms that are fed into AI discovery, leading to a level of speed and in turn scaling drug discovery at an impressive rate. Creating a name for itself AQEMIA moves away from using experimental data and bases the AI powered outcomes on years of data and studies of its now impressive team of 50.

Aqemia’s discoveries have already made an impact in oncology and immuno-oncology trials. The company sets goals to be part of more life changing clinical trials with wholly or partly owned drug candidates and with significant funding continues to scale its platform to continue wins in its research. It will be exciting to see how more research and collaborations like that with Servier (international pharmaceutical company) will continue to grow its success.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 6 rounds)

Apr 2025

$7.4m

GRANT

Dec 2024

$42.3m

EARLY VC

Total funding: $132.2m

Company HQ

Necker, Paris, France

Leadership

Maximilien Levesque

(Co-Founder & CEO)

Currently a Board Member of France Biotech. Founded Personal HPC and worked through several roles at École normale supérieure most recently as a Research Group Leader.

Emmanuelle Martiano Rolland

(Co-Founder & COO)

Previous Principal at Boston Consulting Group after completing a Master of Science Imperial College of London.

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