About this role
Summary: Advance methodological capabilities in advanced data science by conducting applied machine learning research. Investigate emerging methods in LLMs, multimodal learning, and causal ML to support pharmaceutical R&D workflows. Translate research into reference implementations and collaborate with academic and industry...
Work Your Magic with us!
Ready to explore, break barriers, and discover more? We know you’ve got big plans – so do we! Our colleagues across the globe love innovating with science and technology to enrich people’s lives with our solutions in Healthcare, Life Science, and Electronics. Together, we dream big and are passionate about caring for our rich mix of people, customers, patients, and planet. That's why we are always looking for curious minds that see themselves imagining the unimaginable with us.
United As One for Patients, our purpose in Healthcare is to help create, improve and prolong lives. We develop medicines, intelligent devices and innovative technologies in therapeutic areas such as Oncology, Neurology and Fertility. Our teams work together across 6 continents with passion and relentless curiosity in order to help patients at every stage of life. Joining our Healthcare team is becoming part of a diverse, inclusive and flexible working culture, presenting great opportunities for personal development and career advancement across the globe.
Your role:
In this role, you will advance the methodological capabilities of the Advanced Data Science team within the Data Sciences organization. You will conduct applied machine learning research that extends beyond standard off-the-shelf approaches and creates new capabilities for high-value scientific and decision-making workflows across pharmaceutical Research & Development.
You will investigate emerging methods in areas such as large language model reasoning and planning, multimodal representation learning, causal machine learning, digital twins, uncertainty quantification, sequential decision-making, and learning from expert feedback. Your research will address limitations of current AI methods and develop innovative approaches for integrating heterogeneous evidence, modelling complex biological and clinical systems, and supporting decisions under uncertainty.
Working closely with Applied AI Engineers, machine learning experts, software engineers, scientists, and business stakeholders, you will translate promising research into reference implementations and demonstrable capabilities for priority R&D use cases. You will ensure that methodological innovation remains connected to real scientific problems and can progressively be transferred into robust AI-enabled applications.
You will develop and lead research collaborations with academic institutions and external scientific partners, identifying complementary expertise and shaping joint research programs. You will contribute to publications, conference presentations, and other scientific outputs that strengthen the external visibility of the team while supporting the development of differentiated AI capabilities within the organization.
You will work in close partnership with IT, platform, and engineering teams when research methods progress toward broader implementation. Your role will focus on methodological innovation, scientific validation, and translation into use cases, complementing IT ownership of enterprise platforms, infrastructure, cybersecurity, and production operations.
Staying at the forefront of machine learning and artificial intelligence research, you will critically evaluate new methods, reproduce relevant scientific advances, and identify opportunities where new research can create meaningful and measurable impact for pharmaceutical R&D.
Location: Israel
Who you are:
- You hold a PhD in machine learning, artificial intelligence, computer science, statistics, applied mathematics, biomedical engineering, or a related quantitative discipline.
- You have a minimum of 5 years of professional or research experience with a strong research track record in machine learning, demonstrated through high-quality peer-reviewed publications, including contributions to leading conferences such as NeurIPS, ICLR, ICML, or comparable venues. Patents, open-source software, and other high-impact scientific outputs are also valued.
- You possess deep expertise in one or more areas such as foundation models, large language model reasoning, multimodal learning, causal machine learning, digital twins, probabilistic modelling, uncertainty quantification, or sequential decision-making.
- You have experience developing, implementing, and rigorously evaluating novel machine learning methods rather than relying exclusively on existing libraries or commercial AI services.
- You are proficient in Python and modern machine learning frameworks such as PyTorch, JAX, TensorFlow, or equivalent technologies.
- You have experience designing reproducible computational experiments, establishing appropriate baselines, conducting ablation studies, and evaluating methods using scientifically rigorous benchmarks.
- You are able to identify limitations in current state-of-the-art methods and formulate tractable research questions that are relevant to real-world scientific problems.
- You have experience translating research prototypes into reference implementations that can be adopted or further developed by applied AI and software engineering teams.
- You are comfortable working with complex, heterogeneous, and potentially multimodal data, such as clinical, molecular, imaging, real-world, digital health, or scientific data.
- You have experience initiating or contributing to collaborations involving academic researchers, industry scientists, and multidisciplinary technical teams.
- You possess strong scientific communication and writing skills and can communicate methodological concepts clearly to both specialist and non-specialist audiences.
- You combine scientific ambition with a strong interest in translating methodological innovation into practical value.
- Experience in pharmaceutical R&D, healthcare, life sciences, or another regulated scientific environment is considered an advantage.
What we offer: We are curious minds that come from a broad range of backgrounds, perspectives, and life experiences. We believe that this variety drives excellence and innovation, strengthening our ability to lead in science and technology. We are committed to creating access and opportunities for all to develop and grow at your own pace. Join us in building a culture of inclusion and belonging that impacts millions and empowers everyone to work their magic and champion human progress!
Apply now and become a part of a team that is dedicated to Sparking Discovery and Elevating Humanity!