Computational Science Manager – Digital R&D Large Molecule Research

Key Skills

Aartificial intelligence, Algorithms, AWS, Azure, Deep Learning, Effective communication skills, Google Cloud Platform (GCP), Keras software library, Machine learning techniques, matplotlib, NumPy, Python Programming, PyTorch, Reinforcement Learning, Scikit-learn, Statistics, TensorFlow

Job Description

Computational Science Manager – Digital R&D Large Molecule Research

• Location: BE, DE, GB, US
• % Remote working and % of travel expected: 50% remote and limited travel expected
• Job type: Permanent & Full time

About the job

Sanofi has recently embarked on a vast and ambitious digital transformation program. A cornerstone of this roadmap is the acceleration of its data transformation and of the adoption of artificial intelligence (AI) and machine learning (ML) solutions to accelerate R&D, manufacturing and commercial performance, and bring better drugs and vaccines to patients faster, to improve health and save lives.

In alignment to our digital transformation, we have launched a new major strategic initiative in 2023: the Biologics x AI Transformation. This is positioned to be a unique data-driven team, with expertise in AI platforms, data engineering, ML operations, data science, computational biology, strategy, and beyond. We are working as one to identify, design, and scale state-of-the-art AI capabilities targeted to truly transform how we research biologics. 

In this role you will be a dynamic people manager looking to apply cutting-edge computation, machine learning / deep learning approaches to revolutionize our large molecule computational tools by contributing to accelerating and improving the process of design and engineering of novel biologics drug candidates.

Main responsibilities

• Advanced degree (e.g., M.Sc., PhD) in a field related to AI/ML or Data Analytics such as: Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology or Engineering Sciences
• Some years of industry experience with a track record of applying ML/Deep Learning (DL) approaches to solve molecule-related problems is an advantage
• Strong familiarity with protein structure or sequence featurization/embeddings
• Strong familiarity with 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
• Proficiency in Python and deep learning libraries such as PyTorch, TensorFlow, Keras, Scikit-learn, Numpy, Matpilotlib
• Strong familiarity with data visualization and dimensionality reduction algorithms
• Ability to develop, benchmark and apply predictive algorithms to generate hypotheses
• Strong knowledge of AWS cloud computing services (Azure & GCP is a plus) 
• Excellent written and verbal communication, strong tropism for teamwork
• Experience designing, developing, optimizing, and / or maintaining ML/DL approaches to solve molecule-related problems 
• Strong understanding of pharma R&D process is a plus
• Technical knowledge of software application development and agile methodologies 
• Understanding and application of data / digital strategy and governance
• A change agent with a combination of business, science & technology, and diplomatic skills 

About you

• Advanced degree (e.g., M.Sc., PhD) in a field related to AI/ML or Data Analytics such as: Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology or Engineering Sciences is an advantage 
• Familiarity with 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
• Proficiency in Python and deep learning libraries such as PyTorch, TensorFlow, Keras, Scikit-learn, Numpy, Matpilotlib is a plus
• Familiarity 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, strong tropism for teamwork 
• Strong understanding of pharma R&D process is a plus

Pursue progress. Discover extraordinary.

Better is out there. Better medications, better outcomes, better science. But progress doesn’t happen without people – people from different backgrounds, in different locations, doing different roles, all united by one thing: a desire to make miracles happen. So, let’s be those people.

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