Summer 2025 - PhD internship: Applied Machine Learning Genomics
Company: Disability Solutions
Location: Cambridge
Posted on: November 1, 2024
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Job Description:
Working with UsChallenging. 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:
.Position SummaryPseudotime 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
Keywords: Disability Solutions, Nashua , Summer 2025 - PhD internship: Applied Machine Learning Genomics, Other , Cambridge, New Hampshire
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