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We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working\\-with\\-us . \n\n \n\n**Why this role?** \n\n \n\nThe **Predictive Biology \\& AI team** at CITRE (Seville, Spain) is looking for a **Scientist in Machine Learning** to bring both conceptual expertise and practical problem\\-solving to our mission. This role combines technical excellence with independence and leadership potential: you will design solutions to challenging problems, guide projects with manageable risks, and share best practices that strengthen both your team and the wider organisation. \n\n \n\nCITRE is BMS's European hub for computational innovation, where AI is applied across the drug discovery continuum. Here, your work will move beyond theory into real\\-world applications that inform strategy and decision\\-making. \n\n \n\nIn particular, the team is tackling pressing questions in biomedical research, such as:* **How can we build and apply foundation models in oncology and neuroscience** to capture the complexity of disease biology and accelerate drug discovery?\n* **How can multi\\-modal AI methods integrate omics, imaging, and clinical data** to uncover novel disease mechanisms and therapeutic opportunities?\n* **How can predictive biology approaches help anticipate patient responses** and support precision medicine strategies?\n\n\nYour contributions will directly shape how we address these questions, helping transform emerging machine learning technologies into tangible scientific and clinical impact. \n\n \n\n**What you will do*** **Shape research and practice** by applying your expertise in machine learning to biomedical data, providing insights and best practices that address scientific and business challenges.\n* **Work independently** on projects that require collaboration with external partners, contributing to decision\\-making with minimal managerial oversight.\n* **Lead and deliver projects** with clear goals, manageable risks, and appropriate use of resources, ensuring high\\-quality results.\n* **Be a resource for colleagues**, sharing knowledge, mentoring less experienced team members, and helping to build team capacity.\n* **Solve problems creatively** \\- not only applying existing methods but also exercising judgment to adapt and develop new approaches.\n* **Contribute to decisions** whose impact extends across your team, related teams, and external collaborators, ensuring alignment with BMS's broader objectives.\n\n**What you bring*** Ph.D. in Machine Learning, Bioinformatics, Computer Science, Statistics, Applied Mathematics, Physics, Electrical Engineering, or a related field.\n* Applied experience with both established and modern ML methods.\n* Evidence of impactful projects or publications.\n* Proficiency in Python and its scientific ecosystem (Pandas, NumPy, SciPy, scikit\\-learn).\n* Experience with at least one deep learning framework (PyTorch, TensorFlow, or JAX).\n* Ability to communicate results clearly in English, both in writing and speaking.\n* Curiosity for biology and motivation to apply computational skills to healthcare challenges.\n\n**Desirable extras*** Experience with ML applied to digital pathology or radiology (2D and/or 3D).\n* Postdoctoral or equivalent experience in academia or industry (1\\+ years).\n* Familiarity with transformer\\-based models and self\\-supervised learning.\n* Previous work in pharma, biotech, or healthcare research.\n* Experience with multi\\-modal biological datasets (omics, imaging, time\\-series).\n* Comfort with HPC clusters (e.g., SLURM) and software tools like Docker and Git.\n\n\nBristol\\-Myers Squibb is an equal opportunity employer. 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Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues. \n\n \n\n**On\\-site Protocol** \n\n \n\nBMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site\\-essential, site\\-by\\-design, field\\-based and remote\\-by\\-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:\n \n\n \n\nSite\\-essential roles require 100% of shifts onsite at your assigned facility. Site\\-by\\-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. 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