Senior Scientist

At Bristol Myers Squibb, we are inspired by a single vision - transforming patients’ lives through science. In oncology, hematology, immunology and cardiovascular disease - and one of the most diverse and promising pipelines in the industry - each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.

CITRE, based in Seville, Spain, is Bristol Myers Squibb’s research institute in Europe, and our link to the European research community. Informatics & Predictive Sciences at CITRE performs innovative computational research to inform decisions across all stages of drug development. Areas of research include computational and network biology, machine/deep learning, cheminformatics, predictive modeling, patient stratification, and method development for analysis and interpretation of biological data.

**Position**

Biomedical knowledge discovery and data mining refers to the research area focusing on developing methodologies to extract useful biomedical associations, patterns, rules from huge amount of heterogeneous data, including but not limited to biomedical knowledge graph, various databases, and scientific literature.

**Responsibilities**
- Participate in research projects involving the development of cutting-edge graph machine learning algorithms over very large knowledge graphs for the internal drug discovery and development research.
- Collaborate as a member of cross-functional teams to design experiments, guide data generation, and validate in silico findings.
- Author scientific reports and present methods, results, and conclusions to publishable standard

**Qualifications & Experience**
- Ph.D. with AI/ML/NLP/graph machine learning focus in Computer Science, Data Science, Biomedical Informatics, or a related field with a firm grasp of quantitative methods.
- Strong experience in developing supervised and unsupervised machine/deep learning methods, preferably with strong experience in the deep graph neural network and graph embeddings approaches.
- Strong expertise in scientific programming languages (e.g., Python), libraries (e.g., PyTorch, Tensorflow), graph machine learning packages, graph databases, and training/deploying models in a cloud computing environment (preferably with AWS).
- Experience in building time-series predictive model.
- Familiarity with version control services such as GitHub or GitLab. Please include a link to your public repository in the cover letter.
- Problem-solving skills, adaptability and collaborative nature.
- Excellent verbal and written communication skills.
- Fluent English language fluency are prerequisite.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. 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.