Senior Scientist, Bioinformatics

MSD; Cambridge (MA); On-site; USD 80,000 - 120,000; Full time

Job summary

Join a forward-thinking research team as a Spatial Transcriptomics Computational Expert, where you'll leverage your expertise in computational biology and AI/ML to analyze complex datasets. This role offers the chance to work on groundbreaking research in immunological diseases, contributing to novel target identification and drug action mechanisms. You'll develop cutting-edge computational tools, collaborate closely with experimental biologists, and communicate findings effectively. If you're passionate about driving discoveries in a dynamic environment, this opportunity is perfect for you!

Qualifications

• Ph.D. in Computational Biology or related field required.
• Two years of research experience in spatial transcriptomics and data integration.

Responsibilities

• Develop and optimize computational pipelines for spatial transcriptomics data.
• Collaborate with biologists to design analysis strategies and interpret results.

Skills

Computational Biology

Statistical Methods

AI/ML

Bioinformatics

Python

R

Data Visualization

Problem-Solving

Education

Ph.D. in Computational Biology

Tools

Seurat

Scanpy

Git

AWS

Google Cloud

Azure

Job description

Job Description

The Data, AI, and Genome Sciences department is seeking a highly motivated and exceptionally skilled Spatial Transcriptomics Computational Expert to join our Translational Genome Analytics research team based in Cambridge, MA. This individual will play a crucial role in analyzing and interpreting complex spatial transcriptomics datasets generated using various cutting-edge platforms. The ideal candidate will possess a deep understanding of computational biology, statistical methods, AI/ML and bioinformatics pipelines, with a proven track record of independently developing and applying advanced analytical approaches to extract meaningful biological insights from spatially resolved transcriptomic data. This is an exciting opportunity to contribute to groundbreaking research and drive discoveries in complex immunological diseases to inform novel target identification and mechanisms of drug action.

In this exciting role, you will:

• Develop, implement, and optimize computational pipelines for the processing, quality control, normalization, integration, and analysis of spatial transcriptomics data (e.g., 10x Xenium/Visium, Nanostring CoxMx/GeoMx, MERFISH, seqFISH).

• Apply advanced statistical inference and AI/ML methods for

  • Spatial domain identification and characterization.

  • Cell type deconvolution and spatial mapping.

  • Identification of spatially variable genes and pathways.

  • Analysis of cell-cell interactions and spatial relationships.

  • Integration of spatial transcriptomics data with other omics datasets (e.g., single-cell RNA-seq, proteomics, imaging).

• Develop novel computational tools and algorithms to address specific challenges in spatial transcriptomics data analysis.

• Collaborate closely with experimental biologists to understand biological questions, design analysis strategies, and interpret results.

• Effectively communicate complex computational findings to both computational and experimental colleagues through clear visualizations, reports, and presentations.

• Stay up-to-date with the latest advancements in spatial transcriptomics technologies, computational methods, and relevant biological fields.

• Contribute to the preparation of manuscripts, presentations, and intellectual property filings.

• Maintain meticulous documentation of codes, pipelines, and analyses.

Qualifications:

Education:

• Ph.D. in Computational Biology, Bioinformatics, Biostatistics, Computer Science or a related field and relevant experience listed below.

Required Experience and Skills:

• Two (2) years of in-depth research experience with spatial transcriptomics, multi-omics data integration and analysis in such fields as data science, computational biology or bioinformatics.

• Demonstrable strong computational background with extensive experience in programming languages such as Python and R. Proficiency in other languages (e.g., C++, Java) is a plus.

• Deep understanding of statistical principles and AI/ML algorithms relevant to high-dimensional data analysis.

• Proven experience in analyzing large-scale omics datasets, with a strong focus on transcriptomics and ideally including spatial transcriptomics data.

• Hands-on experience with various spatial transcriptomics analysis tools and packages (e.g., Seurat, Scanpy, Squidpy, Giotto, CellProfiler, HALO).

• Experience with cloud computing platforms (e.g., AWS, Google Cloud, Azure) and high-performance computing environments is highly desirable.

• Strong data visualization skills with experience using relevant software packages (e.g., ggplot2, matplotlib, Seurat/Scanpy visualization tools).

• Excellent problem-solving, critical thinking, and analytical skills.

• Strong written and oral communication skills, with the ability to clearly explain complex technical concepts to diverse audiences.

• Ability to work independently and collaboratively within a multidisciplinary team.

Preferred Experience and Skills:

• Experience with image analysis techniques relevant to spatial transcriptomics.

• Knowledge of specific biological domains relevant to the immune mediated disease or oncology in our Company's Research Lab.

• Experience in developing and deploying bioinformatics pipelines.

• Familiarity with database management and data warehousing concepts.

• Experience with version control systems (e.g., Git).

• A strong publication record in peer-reviewed journals

#EligibleforERP

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Employee Status:

Regular

Relocation:

Domestic

VISA Sponsorship:

No

Travel Requirements:

10%

Flexible Work Arrangements:

Not Applicable

Shift:

1st - Day

Valid Driving License:

No

Hazardous Material(s):

No

Job Posting End Date:

06/30/2025

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