Job Description Summary
Location: Cambridge#LI-Hybrid 3 days/week in office
138,600.00 - 198,000.00 - 257,400.00 USD Annual
This role within the Applied AI, Low Molecular Weight (LMW) group of AI4R will contribute to the development, evaluation, and application of AI methods and workflows for LMW drug discovery. Working closely with multidisciplinary project teams, engineers, and other data scientists, the successful candidate will build and benchmark the right AI approaches, algorithms, models and workflows, to maximize impact on key domains areas of biomedical research that will potentially lead to developing better drugs, faster.
Job Description
Purpose of the role
Senior Expert (Applied AI, LMW Drug Discovery):
- Work within a global team of AI researchers and SME with core domain expertise in applying AI to low molecular weight drug discovery.
- Contribute to the conceptualization of AI methods and their applications for hit generation, lead optimization, pre-clinical analysis, including safety and PK/PD
- Develop, adapt and evaluate state-of-the-art AI/machine learning models, including foundation models, generative AI, multimodal AI, and agentic systems
- Establish rigorous evaluation and benchmarking frameworks to assess the robustness and scientific validity of models deployed in drug discovery applications
- Define translatable metrics that connect model performance to downstream scientific decisions, including assay-level or prioritization improvements, and experimental efficiency
- Help integrate of AI approaches into design-make-test-analyze (DMTA) cycles to accelerate LMW drug discovery
- Facilitate delivery of AI solutions through collaboration with Engineering and Product Development teams
- Communicate progress and impact to stakeholders and multidisciplinary audiences
Collaboration & partnership
- A respectful team-player attitude is an absolute must
- Regularly communicate, engage, align with AI4R teams, broader data science community, and senior scientists
- Collaborate cross-functionally (medicinal chemists, DMPK, structural biology, and disease-area scientists, engineers and other AI experts) complementing complex projects with AI-based approaches to LMW drug discovery
- Excellent interpersonal and communication skills, with ability to translate analytical concepts for diverse audience and stakeholders (English is our primary language)
What you’ll bring to the role:
- A deep curiosity and passion for biomedical sciences driven therapeutic discovery.
- 4+ years of significant experience in innovation, development, deployment and continuous support of Machine Learning data management and modeling
- Strong hands-on coding proficiency in Python and deep learning frameworks
- Strong understanding and experience in using version control systems for developing software (e.g. GitHub, git, subversion, bitbucket, etc.)
- Demonstrated expertise / experience in several of molecular AI/ML areas, such as generative chemistry; structure-based drug design across hit finding, hit to lead, lead optimization, and candidate selection; protein-ligand modelling, co-folding; docking, scoring, and pose assessment with rigorous model validation and tight coupling to experimental follow up; QSAR; multi-objective property optimization (uncertainty estimation, active learning concepts); free energy and affinity prediction
- Demonstrated expertise / experience with AI driven molecular design applied to the areas above· Experience working in a large Research organization & deep understanding of drug development a plus
- Passion for understanding emerging technologies with pragmatic insight into where those technologies can be integrated into business solutions
- Ability to balance requirements, manage expectations, and drive effective results using a proactive attitude towards identifying and resolving issues
- Strong organizational and problem-solving skills, with ability to execute and prioritize well in a complex matrixed environment.
Relevant areas of desired expertise:
Molecular representation learning for small molecules, graph neural networks, geometric deep learning, property prediction for ADME PK, physiochemical properties, safety, de novo design, chemical space exploration, foundation models for chemistry, uncertainty quantification, active learning, agentic AI, generative chemistry, counterfactuals and explainability, multi-objective optimization.
EEO Statement:
The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.
Accessibility and reasonable accommodations
The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to [email protected] or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.
Salary Range
$138,600.00 - $257,400.00
Skills Desired
Artificial Intelligence (AI), Biostatistics, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series AnalysisSkills Required
- 4+ years of experience developing, deploying, and supporting machine learning, data management, and modeling solutions
- Strong hands-on coding proficiency in Python and deep learning frameworks
- Strong understanding and experience using version control systems such as GitHub, Git, Subversion, or Bitbucket
- Expertise in molecular AI/ML, including generative chemistry, structure-based drug design, protein-ligand modeling, docking, QSAR, property optimization, or free-energy prediction
- Experience applying AI-driven molecular design to hit generation, lead optimization, candidate selection, or related drug-discovery workflows
- Experience with molecular representation learning, graph neural networks, geometric deep learning, ADME/PK prediction, uncertainty quantification, active learning, foundation models, or agentic AI
- Experience working in a large research organization and deep understanding of drug development
- Strong organizational, problem-solving, communication, collaboration, and stakeholder-management skills
Novartis Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Novartis and has not been reviewed or approved by Novartis.
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Healthcare Strength — Pay and benefits are described as a strong overall package, supported by medical, dental, and vision insurance alongside FSAs/HSAs and disability and life coverage. Mental-health support is reinforced through an employee assistance program with psychological support and a network of mental health first aiders.
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Retirement Support — Retirement support is positioned as a standout element, with an automatic company contribution plus dollar-for-dollar matching in the 401(k). Additional retirement funding is described through an age-based defined contribution program and access to an employee share purchase plan discount.
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Parental & Family Support — Family-related benefits are framed as robust, including a global minimum of paid parental leave for new parents following birth or adoption. Added supports include domestic partner coverage, dependent-care resources, and benefits such as adoption assistance and child/elder care options.
Novartis Insights
What We Do
Novartis is an innovative medicines company. Every day, working to reimagine medicine to improve and extend people’s lives so that patients, healthcare professionals and societies are empowered in the face of serious disease. Our medicines reach more than 250 million people worldwide.









