Job Description Summary
About the role:
Job Description
Key responsibilities:
Design, develop, implement and apply advanced machine learning algorithms, AI models, and platforms to enable the delivery of predictive insights from pre-clinical, clinical and real-world evidence datasets.
Demonstrate value of innovative AI techniques in the context of drug target identification, biomolecular interaction modeling, drug development, biomarker discovery, treatment response prediction and clinical trial design.
Work with foundational models, including pre-trained, self-supervised, multi-purpose, and multi-modal models to advance generative AI applications in drug discovery.
Collaborate with cross-functional teams to develop and adopt best practices for ML-ready data.
Contribute to scientific publications and present results at internal and external scientific conferences.
Minimum Requirements:
This position will be located at either the Cambridge, MA or Basel, Switzerland site and will not have the ability to be located remotely. This position will require 0-3% travel as defined by the business (domestic and/ or international).
MSc or Ph.D. in Machine Learning, Computer Science, Applied Mathematics, Computational Biology or related field; PhD preferred.
Minimum of 0-3 years of experience.
Strong experience in one or more of the following areas: generative AI, agentic AI, biomedical foundation models, geometric deep learning, multi-modal learning, and large-scale knowledge graphs.
Excellent programming skills and proficiency in deep learning frameworks (PyTorch), with openness to learning new tools and technologies.
Practical experience across ML and Large Language Models (LLMs) software stack, including feature engineering, model development, deployment, and validation.
Prior experience working with omics data and familiarity with oncology drug development.
Excellent communication skills, with the ability to communicate complex data insights and recommendations to cross-functional teams and stakeholders.
Demonstrated strong research skills, evidenced by publications in top-tier machine learning or artificial intelligence conferences and/or leading scientific journals.
The salary for this position is expected to range between $103,600 and $192,400 per year.
The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.
Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.
US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.
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 us.reasonableaccommodations@novartis.com 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
$103,600.00 - $192,400.00
Skills Desired
Biostatistics, Computer Programming, Data Analysis, Databases, Data Management, Data Mining, Data Quality, Data Visualization, Deep Learning, Graph Algorithms, High-Performance Computing, Logistic Regression Model, Machine Learning (Ml), Master Data Management, Pandas (Python), Python (Programming Language), R (Programming Language), Random Forest Algorithm, Sql (Structured Query Language), Statistical Modeling, Time Series Analysis