Computational Scientist
Cambridge, United Kingdom
Sanofi
Sanofi pushes scientific boundaries to develop breakthrough medicines and vaccines. We chase the miracles of science to improve people’s lives.- Location: Cambridge, UK
- Alternative locations: Frankfurt am Main, GE or Ghent, BE
- Hybrid Work - 60% office based, 40% remote
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: the Biologics x AI Moonshot (BioAIM). 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.
Who You Are:
You are a dynamic Computational Scientist who will work with other scientists to apply cutting-edge 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.
We are an innovative global healthcare company with one purpose: to chase the miracles of science to improve people’s lives. We’re also a company where you can flourish and grow your career, with countless opportunities to explore, make connections with people, and stretch the limits of what you thought was possible. Ready to get started?
Main responsibilities:
- Apply and develop artificial intelligence and machine learning (AI/ML) approaches (e.g. classification, clustering, machine learning, deep learning) on pharma research data sets (e.g. activity, function, ADME properties, physico-chemical properties, etc.).
- Building models from internal and external data sources, and performance evaluation by writing code and using state-of-the art machine learning technologies.
- Close interactions with other Computational scientists, data engineers, software engineers, UX designers, as well as research scientists in core scientific platforms focusing on protein therapeutics, in an international context.
- Update and report relevant results to interdisciplinary project teams and stakeholders.
- Maintain a keen awareness of recent developments in data science and bioinformatics and state-of-the-art of AI/ML/DL algorithms and research results
- Active engagement in evaluation and coordination of both academic and startup collaborations as well as outsourcing partners.
About you:
- PhD degree in a field related to AI/ML or Data Analytics such as: Computer Science, Mathematics, Statistics, Physics, Biophysics, Computational Biology or Engineering Sciences.
- Relevant industry experience with a track record of applying ML/Deep Learning (DL) approaches to solve molecule-related problems.
- 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.
- Comfortable working in cloud and high-performance computational environments (e.g. AWS, SageMaker).
- Excellent written and verbal communication, strong tropism for teamwork.
- Strong understanding of pharma R&D process is a plus.
Why choose us?
- Bring the miracles of science to life alongside a supportive, future-focused team.
- Discover endless opportunities to grow your talent and drive your career, whether it’s through a promotion or lateral move, at home or internationally.
- Enjoy a thoughtful, well-crafted rewards package that recognizes your contribution and amplifies your impact.
- Take good care of yourself and your family, with a wide range of health and wellbeing benefits including high-quality healthcare, prevention and wellness programs and at least 14 weeks’ gender-neutral parental leave.
Visas for those who do not already have the right to work in the UK will be considered on a case by case basis according to business needs and resources.
#LI-EUR
Pursue progress, discover extraordinaryBetter 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, ability or gender identity.
Watch our ALL IN video and check out our Diversity Equity and Inclusion actions at sanofi.com!
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Bioinformatics Biology Classification Clustering Computer Science Data Analytics Data visualization Deep Learning Engineering GANs Keras Machine Learning Mathematics NumPy Pharma PhD Physics Python PyTorch R R&D Reinforcement Learning Research SageMaker Scikit-learn Statistics TensorFlow Transformers UX
Perks/benefits: Career development Equity / stock options Health care Parental leave Startup environment Wellness
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.