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Position Summary
We are seeking a highly motivated student to join our group for a 10-week long summer internship program. A successful candidate will work with the team to develop a statistical learning method to infer regulon and protein activity that capture the effect of somatic alterations in regulatory proteins.
Identifying causal drivers of cancer progression is essential for developing effective anti-cancer therapies. Our team has a strong background in inferring protein regulatory activity, which we will leverage in this project. We integrate multi-modal real-world patient data (RWD) to identify key drivers that drive and maintain patient states via regulating key oncogenic processes and transcriptional programs. These drivers represent best opportunity for therapeutic intervention due to their disease relevant regulatory roles. However, many existing approaches to identify these drivers rely solely on expression relationships between gene pairs, ignoring somatic alterations that are common in cancers and often independently affect regulator activity that is not captured in gene expression data.
In this summer intern project, we propose to build on existing internal methods aimed at capturing transcriptional regulatory relationships. We will focus on enhancing and strengthening the signal across different biological contexts. Specifically, we will develop a statistical learning method to infer regulon and protein activity that capture the effect of somatic alterations in regulatory proteins. This new method may uncover novel therapeutic targets with clear patient selection, which are missed by existing methods.
Key Responsibilities
Develop a novel statistical model that integrates transcriptomic and somatic alteration data to infer regulons for driver genes. The inferred protein activity will capture the effect of somatic alterations in those regulatory proteins.
Benchmark the performance this method in colorectal cancer (CRC) by evaluating key biological pathways using gene signatures and CPTAC phosphoprotein data.
Cross-validate driver-regulon inference results between different patient cohorts
Qualifications & Experience
Currently enrolled in a Ph.D. program in bioinformatics, biostatistics, computer science or a similar quantitative field
A strong foundation in statistical model and machine learning methods
Proficient in R (for data analysis and visualization)
Experienced in transcriptomic data analyses
Excellent communication and presentation skills
The starting compensation for this job is a range from $35.00/hour - $43.00/hour. The starting pay rate takes into account characteristics of the job, such as required skills and the geographic location where work is performed. Final individual compensation is decided commensurate with demonstrated experience and education level.
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.
Uniquely Interesting Work, Life-changing Careers
With a single vision as inspiring as "Transforming patients' lives through science™ ", every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in an inclusive culture, promoting diversity 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.
On-site Protocol
BMS has a diverse 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:
Site-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. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.
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