Biomedical Machine Learning Innovation Scientist at Novartis

Cambridge, Basel-City, Switzerland -

Full Time

Start Date

Immediate

Expiry Date

07 Feb, 26

Salary

0.0

Posted On

09 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Apache Hadoop, Applied Mathematics, Big Data, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning, Machine Learning Algorithms, Proteomics, Python, R, Statistical Modeling

Industry

Pharmaceutical Manufacturing

Description

Job Description Summary Novartis has embraced a bold strategy to drive a company-wide digital transformation. Our objective is to position Novartis as an industry leader by proactively adopting digital technologies that foster innovative approaches to hasten drug discovery and development. By utilizing both internal and external Research & Development data with the power of data science, predictive models, generative AI, and machine learning, our objective is to identify new targets, create more effective therapeutic molecules, better predict drug pharmacokinetics and safety risks, refine clinical trial design, and significantly shorten development cycles. The Artificial Intelligence & Computational Sciences (AICS) team leads Biomedical Research (BR) in exploring and applying advanced AI and ML methodologies to generate novel drug discovery insights, and to speed and improve drug discovery efficiency whilst focusing on patients’ needs. AICS partners with drug discovery teams, raises the level of AI expertise across BR and ensures that BR science keeps up with the rapidly evolving ecosystem of AI technologies by connecting with AI leaders in academia and industry. This role within the Scientific Innovation group of AICS will be tasked with ensuring scientific rigor and innovation for AI applications and methods for drug discovery. Additionally, the role would be expected to act as the SME liaison of AICS to BR Disease Areas (DAs) and Function Areas (FAs). Job Description Responsibilities: Scientific Innovation Senior Expert: Work with a team of AI researchers and SMEs with core domain expertise in applying AI to drug discovery. Work with AI modelers to ensure models are robust and performant Work with Engineering and Product Development resources to ensure delivery of AI solutions. Raise the awareness of AI applications to aid in answering key research questions across BR. Help position AI-aided drug discovery contributions to deliver and support progress of BR’s portfolio, enable new kinds of therapeutic discoveries, shorten cycle times, and increase efficiency. Collaboration & partnership: Act as liaison of AICS for identification of research questions, solution design, and evangelism of results and impacts of AI across BR Regularly communicate, engage, align with AICS teams, broader data science community, and senior scientists. Initiate and lead key high-value internal collaborations across BR. Help design translatable metrics for AI models that will lead to tangible impact in collaboration with BR DAs and FAs. Essential Requirements: 4+ years of significant experience in innovation, development, deployment and continuous support of Machine Learning data management and modeling, including experience in an Enterprise environment Specialization in at least one of the core drug discovery functional areas like target identification, computational chemistry, protein structure modelling and design or translational medicine. Expertise in bringing advanced analytics insights and actions to a large Research organization & deep understanding of Drug development. Entrepreneurial spirit with can-do, pro-active attitude which compliments your 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, problem-solving, and influencing skills and demonstrated track record of exceptional teamwork. Functional leadership capability with excellent interpersonal, communication, and presentation skills. Commitment to Diversity & Inclusion: We are committed to building an outstanding, inclusive work environment and diverse teams representative of the patients and communities we serve. Benefits and rewards: Read our handbook to learn about all the ways we’ll help you thrive personally and professionally: https://www.novartis.com/careers/benefits-rewards For Basel, Switzerland: Switzerland Accessibility and accommodation Novartis is committed to working with and providing reasonable accommodation to all individuals. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the recruitment process, or in order to receive more detailed information about the essential functions of a position, please send an e-mail to diversity.inclusion_ch@novartis.com and let us know the nature of your request and your contact information. Please include the job requisition number in your message. Skills Desired Apache Hadoop, Applied Mathematics, Big Data, Curiosity, Data Governance, Data Literacy, Data Management, Data Quality, Data Science, Data Strategy, Data Visualization, Deep Learning, Machine Learning (Ml), Machine Learning Algorithms, Master Data Management, Proteomics, Python (Programming Language), R (Programming Language), Statistical Modeling Improving the lives of people living with disease takes more than innovative science. It takes a focus on the needs of people and a community committed to meeting them. It takes a team of people like you. Working together. Learning together. Thriving together. Discover how you can join us in changing people’s lives. In the context of China Cross-Border Data Transfer (CBDT) policy, if you need to apply for a position in China, please go to the local Recruiting System TaleNov .

Responsibilities

The role involves working with a team of AI researchers and subject matter experts to apply AI to drug discovery, ensuring models are robust and effective. Additionally, it includes acting as a liaison for identifying research questions and promoting AI applications across Biomedical Research.