Computational Scientist – (Machine Learning) Digital R&D Large Molecule Research

• Location: Ghent, Belgium
• Remote working and travel expected: 50% remote with minimal expected travel
• Job type: Full time & Permanent

About the job

This is a new internal opportunity in Ghent for a Computational Scientist. Sanofi has recently started an expansive and ambitious digital transformation program. A key part of this program is to accelerate data transformation and the adoption of artificial intelligence (AI) and machine learning (ML) solutions in order to improve R&D, manufacturing, and commercial performance, ultimately delivering better drugs and vaccines to patients faster and saving lives.

Aligned with our digital transformation, in 2023 we initiated a significant strategic project - the Biologics x AI Transformation. This team has been created to be a unique, data-driven team, with expertise in AI platforms, data engineering, ML operations, data science, computational biology, strategy, and more. We work together to identify, design, and scale cutting-edge AI capabilities specifically targeted at transforming our biologics research.

In this role, you will work with other scientists to apply advanced computation, Machine Learning/Deep Learning approaches to revolutionize our large molecule computational tools, contributing to the acceleration and improvement of the design and engineering process of novel biologics drug candidates.

Main responsibilities

• Apply and develop artificial intelligence and machine learning (AI/ML) methods (e.g., classification, clustering, machine learning, deep learning) to pharmaceutical research datasets (e.g., activity, function, ADME properties, physical-chemical properties, etc.)
• Build models using internal and external data sources, create algorithms, perform simulations, and evaluate performance using cutting-edge machine learning technologies
• Work closely with other Computational scientists, data engineers, software engineers, UX designers, as well as research scientists in core scientific platforms focusing on protein therapeutics, collaborating globally (US, Europe, China)
• Report and update relevant results to interdisciplinary project teams and stakeholders

About you

• An advanced degree (e.g., M.Sc., Ph.D.) related to AI/ML or Data Analytics such as Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology, or Engineering Sciences is advantageous
• Experienced in advanced statistics, ML/DL techniques including various network architectures (CNNs, GANs, RNNs, Auto-Encoders, Transformers, PLM etc.), regularization, embeddings, loss-functions, optimization strategies, or reinforcement learning techniques
• Skilled in Python and deep learning libraries such as PyTorch, TensorFlow, Keras, Scikit-learn, Numpy, Matplotlib
• Experience with data visualization and dimensionality reduction algorithms
• Ability to develop, benchmark, and apply predictive algorithms to generate hypotheses
• Comfortable working in cloud and high-performance computational environments (e.g., AWS)
• Excellent written and verbal communication skills with team-centric mindset
• A strong understanding of the pharmaceutical R&D process is advantageous

Pursue progressiveness. Discover extraordinariness.

Better is out there - better medicines, outcomes, and science. But progress cannot happen without people; individuals from various backgrounds, in differing locations, undertaking diverse roles, all united by a mutual desire to achieve extraordinary things. Let's be those people.

At Sanofi, we deliver equal opportunities to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity.

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At Sanofi, diversity and inclusion are fundamental to our functions and enshrined within our Core Values. We understand that truly harnessing the richness that diversity brings, we must lead inclusively, fostering a workplace environment where differences are celebrated and leveraged to empower the lives of our employees, patients, and customers. We respect and commemorate the diversity of our workforce, their experiences, and backgrounds and provide equal opportunity for all.