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Single Cell Spatial Transcriptomics Jobs in Massachusetts

Research Lab Tech I

Charlestown, MA · On-site

$21 - $29.01/hr

Experience with single-cell RNA-seq, ATAC-seq, WGS, or spatial transcriptomics platforms. * Familiarity with handling and processing human tissues. * Prior exposure to next-generation sequencing ...

... bulk and single-cell, spatial transcriptomics, methylation, imaging) * Credible as a thought partner with senior R&D leaders on patient-centered prediction topics; able to engage across both ...

... bulk and single-cell, spatial transcriptomics, methylation, imaging) * Credible as a thought partner with senior R&D leaders on patient-centered prediction topics; able to engage across both ...

Showing results 21-40

Single Cell Spatial Transcriptomics information

What are the key skills and qualifications needed to thrive as a single cell spatial transcriptomics scientist, and why are they important?

To thrive as a Single Cell Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree (PhD or MSc) in a relevant field. Familiarity with high-throughput sequencing platforms, spatial transcriptomics technologies (like 10x Genomics Visium or NanoString GeoMx), and data analysis tools such as R or Python is essential. Critical thinking, problem-solving, and effective communication are crucial soft skills for interpreting complex data and collaborating in multidisciplinary teams. These skills and qualities are vital for generating reliable insights into cellular function and spatial organization, which drive innovative research and discovery.

What are the typical challenges faced by professionals working in single cell spatial transcriptomics, and how can they be addressed?

Professionals in Single Cell Spatial Transcriptomics often encounter challenges related to handling large, complex data sets and integrating spatial information with single-cell transcriptomic profiles. These tasks demand strong computational skills and close collaboration with bioinformaticians and other researchers. Effective communication within interdisciplinary teams is essential to ensure experimental design aligns with downstream analysis needs. Staying updated with rapidly evolving technologies and best practices also helps professionals overcome technical hurdles and produce reliable, high-impact results.

What is single cell spatial transcriptomics?

Single cell spatial transcriptomics is a cutting-edge technique that allows researchers to analyze gene expression in individual cells while preserving their spatial location within a tissue. This method combines the high-resolution insights of single-cell RNA sequencing with spatial information, enabling scientists to understand how cells interact and organize within their native environments. It is widely used in biomedical research to study tissue architecture, disease mechanisms, and cellular heterogeneity.
What job categories do people searching Single Cell Spatial Transcriptomics jobs in Massachusetts look for? The top searched job categories for Single Cell Spatial Transcriptomics jobs in Massachusetts are:
What cities in Massachusetts are hiring for Single Cell Spatial Transcriptomics jobs? Cities in Massachusetts with the most Single Cell Spatial Transcriptomics job openings:
Infographic showing various Single Cell Spatial Transcriptomics job openings in Massachusetts as of August 2026, with employment types broken down into 1% Locum Tenens, 1% As Needed, 77% Full Time, 18% Part Time, and 3% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution.

Team Leader in Data Science, Disease Area X

Novartis

Cambridge, MA • On-site

Full-time

Medical, Life, Retirement, PTO

Posted 15 days ago


Novartis rating

7.5

Company rating: 7.5 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

64th of 86 rated pharmaceutical


Job description

Job Description Summary

The Team Leader in Data Science, Disease Area X at Novartis will lead and contribute to high-impact data science programs that transform complex biological, translational, and multi-omics data into decision-driving insights for drug discovery. This role will combine scientific leadership, hands-on computational expertise, and people leadership to advance target identification, biomarker discovery, mechanism-of-action understanding, and portfolio decisions.
The successful candidate will lead a multidisciplinary team of data scientists and partner closely with biology, translational research, data sciences, IT, and discovery platform teams. They will help define and operationalize AI/ML strategy for discovery applications, including generative and agentic AI. This leader will also contribute significantly to data generation, curation, and engineering strategies that enable scalable use of proprietary and public datasets. The role reports to the Head of Data Science, Disease Area X.


Job Description

Internal Job Title: Senior Principal Scientist or Associate Director

Position Location: Cambridge, MA Hybrid

Key responsibilities:

  • Lead data science strategy and executionfor hypothesis-driven discovery programs, including study design, analysis of experiments, and interpretation of complex biological datasets.

  • Drive multi-omics analyticsacross genomics, transcriptomics, proteomics, single-cell, spatial, imaging, clinical, and other relevant data modalities to support target and biomarker portfolios.

  • Translate scientific questions into computational strategies, selecting fit-for-purpose statistical, machine learning, AI, and bioinformatics approaches.

  • Operationalize responsible use of generative and/or agentic AI tools in drug discovery workflows, ensuring scientific rigor, data governance, and appropriate human oversight.

  • Contribute hands-on technical workin scientific software development, data engineering, workflow automation, reproducible analysis, and scalable analytical pipelines.

  • Partner cross-functionallywith wet-lab scientists, translational researchers, platform teams, and senior stakeholders to shape experimental design and accelerate decision-making.

  • Prioritize resources and capabilitiesacross multiple projects, adapting to evolving portfolio needs and balancing strategic impact with delivery timelines.

  • Lead, coach, and develop direct reports, creating a collaborative, inclusive, scientifically rigorous, and high-performing team environment.

  • Communicate scientific findings and recommendationsclearly through internal presentations, governance discussions, publications, posters, and external scientific forums.

  • Promote FAIR data practices, reproducible research, high-quality documentation, project tracking, and scalable analytical standards across the team.

Essential Requirements:

  • Advanced degree (PhD preferred) in Data Science, Computational Biology, Bioinformatics, Computational Science, Molecular Biology, Genetics, Biochemistry, Engineering, or a related quantitative or life sciences discipline.

  • 6+ years of relevant experience applying computational biology, bioinformatics, AI/ML, statistics, or data science to drug discovery, translational research, biotechnology, pharmaceutical R&D, technology, or academic research.

  • Experience leading or managing internal data scientists, computational biologists, bioinformaticians, or machine learning scientists in a matrix management environment as well as external collaborators

  • Demonstrated ability to lead complex, hypothesis-driven scientific analyses using biological, multi-omics, or translational datasets, including RNA-seq, single-cell RNA-seq, proteomics, genomics, spatial biology, and/or imaging.

  • Strong practical experience with scientific software development, reproducible analysis, workflow orchestration and collaborative development practices; experience in Python and/or R, with familiarity in tools such as GitHub, HuggingFace, workflow managers, Jupyter notebooks, containers

  • Deep experience with cloud-based or enterprise-scale compute platforms, high-performance computing

  • Significant experience influencing and collaborating across diverse scientific teams, including wet-lab biology, translational research, engineering, and computational functions.

  • Familiarity with modern AI/ML methods and their application to biological or biomedical data (i.e. generative, agentic AI)

  • Experience acquiring, curating, and engineering proprietary and public datasets while maintaining appropriate data governance, privacy, and security standards.

  • Demonstrated ability to shape scientific strategy cross-functionally, influence senior stakeholders, and translate analytical results into portfolio-relevant decisions.

  • Track record of scientific impact through publications, conference presentations, internal decision support, or portfolio contributions.

  • Strong communication, interpersonal, ethical judgment, resilience, and self-awareness skills.

Compensation & Benefits:

The salary for this position is expected to range between $160,300 and $297,700 USD annually for Senior Principal Scientist, Data Science, and $176,400 and $327,600 USD annually for Associate Director, Data Science. The final salary offered is determined based on factors like, but not limited to, relevant skills andexperience, and upon joining Novartis will be reviewed periodically. Novartis may change the publishedsalary range based on company and market factors.


Your compensation will include a performance-based cash incentive and, depending on the level of therole, eligibility to be considered for annual equity awards.


US-based eligible employees will receive a comprehensive benefits package that includes health, life anddisability benefits, a 401(k) with company contribution and match, and a variety of other benefits. Inaddition, employees are eligible for a generous time off package including vacation, personal days,holidays and other leaves.


To learn more about the culture, rewards and benefits we offer our people click here.


EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status.


Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or to perform the essential functions of a position, please send an e-mail to us.reasonableaccommodations@novartis.com or call +1(877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.


Salary Range

$160,300.00 - $297,700.00


Skills Desired

Artificial Intelligence (AI), Biostatistics, Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Python (Programming Language), Stakeholder Engagement, Statistical Analysis, Time Series Analysis

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