**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 rich in diversity. 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 . **Position Summary** Pseudotime trajectory analysis is widely used to infer differentiation paths such as disease progression. However, traditional methods designed for scRNA-Seq data do not account for the spatial location of cells since the data is generated from dissociated tissues. This lack of contextual information may cause the method to overlook region-specific changes, especially when the same cell type is distributed across different regions. Now there is an opportunity to address this gap with the advent of spatial transcriptomics (ST) technologies, which generate whole transcriptome profiles linked to physical location and tissue morphology. By incorporating spatial information, we expect to reconstruct more accurate and biologically faithful trajectories, enabling the identification of potential targets that drive the progression of disease states. In this internship, we aim to review published spatial trajectory analysis methods, compare one or two methods with a baseline model, and test it on well-characterized ST datasets. This project offers a unique opportunity to contribute to innovative target identification approaches while working alongside a dynamic and collaborative team at BMS. Interns will gain hands-on experience working with large-scale ST data and cutting-edge methods at the interface between machine learning and computational biology. They will also acquire biological insights into complex diseases by learning from bench biologist colleagues. Additionally, interns will have the chance to connect with colleagues across different teams, providing a broader understanding of drug development and hopefully helping to shape their future career plans. **Key Responsibilities**
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