Senior Scientist in ML Methods for Spatial Biology

Job description

Working with Us Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible. 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. Read more: careers.bms.com/working-with-us. When you join BMS, you are joining a high-achieving team united by a common mission. The Informatics and Predictive Sciences (IPS) mission is to Pioneer, Partner and Predict to drive transformative insights for patient benefit. IPS conducts applied computational research in areas that include genomic, structural and molecular informatics, computational and systems biology, patient selection and translational biomarker research, and broader fields including knowledge science, epidemiology and machine learning—across the full lifecycle of drug discovery and development and across all therapeutic areas at BMS. We do this in close partnership with scientific and clinical experts in the field, both inside and outside the company. We perform innovative science to empower key data-driven decisions across a rich pipeline of next-generation medicines. In doing so, our work transforms the lives of patients, as well as our own lives and careers. Here, you’ll get the chance to grow and thrive through opportunities that are uncommon in scale and scope. You’ll pursue innovative ideas while advancing professionally alongside some of the brightest minds in biopharma. Senior Scientist in ML Methods for Spatial Biology Within the Predictive Biology and AI team, we are seeking enthusiastic candidates for a Senior Scientist position focused on applying modern computational and machine learning methods to spatial biology and related life sciences data. The successful candidate will have a strong research background, a track record of independent scientific contributions, relevant publications, experience solving technical problems creatively, and the ability to implement, evaluate, and adapt computational methods based on current research. The successful candidate will be based in Cambridge, MA or Lawrenceville, NJ and will serve as scientific partner for experimental and computational collaborators focused on translational research at those sites while being a member of a geographically distributed team of exceptional machine learning researchers. This role requires strong communication skills, comfort working independently in a distributed environment, and a proactive approach to building productive scientific relationships across disciplines and locations. The candidate will work as part of a multidisciplinary team focused on bringing advanced ML/AI approaches to impactful biological questions. They will collaborate with computational and experimental scientists with expertise in machine learning, structural biology, chemistry, cell therapy, and gene therapy. We encourage applications from candidates with a background in computational method development and an interest in applying innovative computational approaches to life sciences data. The Role Participate in a growing effort to apply advanced computational techniques to the development of novel therapies for neurologic disease, cancer, and hematologic malignancies. Act as a local scientific partner and point of connection for experimental and computational collaborators at the Cambridge or Lawrenceville site, enabling effective cross-functional collaboration with a primarily Europe-based team. Analyze spatial and other omics data, including spatial transcriptomics, single-cell RNA-seq, ATAC-seq, and related data types. Develop, refine, and evaluate computational methods, ML models, and workflows for large biological datasets. Formulate translational and discovery questions as computational problems, interpret model outputs in biologically meaningful ways, and generate hypotheses that can guide experimental biology. Creatively propose hypotheses and test them rigorously. Author scientific reports and present methods, results, and conclusions to a publishable standard. Basic Qualifications Bachelor's Degree 7+ years of academic / industry experience Or Master's Degree 5+ years of academic / industry experience Or PhD 2+ years of academic / industry experience Preferred Qualifications Ph.D. in machine learning, bioinformatics, computational biology, or a related technical field. Experience applying contemporary computational methods to biological problems. Publication record in relevant conferences or journals. Experience applying and/or developing ML methods to bioimaging, bioinformatics, single-cell omics, or spatial omics problems. Experience with at least one ML framework, such as scikit-learn, PyTorch, or TensorFlow. Fluency in written and spoken English. Intense curiosity about the biology of disease and eagerness to contribute to interdisciplinary scientific and computational efforts. Demonstrated ability to work independently in a distributed team environment, with strong communication skills and a proactive approach to cross-functional collaboration. For senior scientist, two or more years of postdoctoral experience in a relevant field. Experience analyzing clinical trial-derived data or images to address translational research questions or applying omics data analysis to public datasets for target discovery and prioritization. Prior research experience in pharma, biotech, academic, or hospital environments. Experience managing multimodal data, including omics, imaging, or time-series signals. Experience using cloud-based computing and software engineering tools or frameworks, such as Docker or Git. Around the world, we are passionate about making an impact on the lives of patients with serious diseases. Empowered to apply our individual talents and diverse perspectives in an inclusive culture, our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues. 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. If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career. Compensation Overview: Cambridge Crossing: $148,210 - $179,601 Princeton - NJ - US: $128,890 - $156,179 The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience. Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/. Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enro