Associate Principal Scientist - Immunology Spatial Omics Analytics

Job Description

The Data, AI, and Genome Sciences department is seeking an experienced and talented computational biologist with expertise in computational analyses of spatial multi-omics data to join our Translational Genome Analytics research team based in Cambridge, MA. We are looking for a data scientist who will leverage advanced statistical inference and AI/ML approaches to integrate patient-derived spatially resolved multi-omics data to decode cellular and molecular mechanisms underlying complex immunological diseases to inform novel target identification and mechanisms of drug action.  

In this exciting role, you will:

• Conduct comprehensive computational analyses of spatial multi-omics data generated from patient-derived tissues to decode cell-type specific molecular networks and molecular crosstalk between cells underpinning immunological diseases such as Inflammatory Bowel Disease, Rheumatoid Arthritis, Systemic Sclerosis, etc.

• Utilize advanced statistical methods and AI/ML techniques to interpret spatially-resolved gene and protein expression patterns, cellular interactions, and tissue architecture as measured by spatial biology platforms such as Xenium, Visium, CosMx, MERFISH, etc.

• Identify and establish cutting edge computational frameworks for spatial multi-omics integrative analyses, including spatially variable gene detection, decoding of cellular and transcriptomic niches and cell-cell interactions (e.g. GraphSAGE, SPARK-X, Spatial DE2, MERINGUE, Spacia, etc)

• Employ statistical modeling approaches to integrate spatial multi-omics data with other omics data layers (e.g. scRNAseq, proteomics, metabolomics, etc) to rigorously decipher cellular functions and to link disease relevant molecular alterations to specific cell types.

• Create visualizations and reports that effectively communicate analytical results with computational and experimental scientists while ensuring statistical rigor, data quality and consistency.

• Collaborate with cross-disciplinary teams, including biologists, clinicians, and other scientists, to address complex biological questions and optimize experimental design

• Mentor and provide guidance to other data scientists on best practices in data analysis, pipeline development, and scientific communication.

• Contribute to the strategic direction of research initiatives by identifying opportunities for funding, partnerships, and innovative methodologies.

• Publish research findings in high-impact peer-reviewed journals, present at scientific conferences, and communicate results to both technical and non-technical audiences.

Required Experience and Skills:

• Ph.D. in Bioinformatics, Computational Biology, Molecular Biology, or a related field with a strong focus on spatial transcriptomics and multi-omics data integration and analysis.

• A minimum of 4 years of postdoctoral or industry research experience in bioinformatics, particularly in leveraging spatial transcriptomics and multi-omics analysis.

• Hands-on experience with computational methods for integrating spatial and multi-omics datasets generated using spatial biology technologies (e.g., Visium, Xenium, CosMx, MERFISH, etc).

• Proven track record of applying machine learning algorithms and advanced computational methods to analyze spatial transcriptomics data, single-cell RNA sequencing (scRNAseq) data, leading to the identification of novel patterns, cell populations, and functional insights

• Extensive experience in bioinformatics tools and programming languages (e.g., R, Python) for data analysis, visualization, and pipeline development

• Proficiency in statistical analysis and machine learning techniques for biological data interpretation.

• Excellent analytical and problem-solving capabilities, with meticulous attention to detail.

• Knowledge of databases and data management systems relevant to biological research.

• Familiarity with cloud-based platforms for scalable data processing and analysis.

• Strong communication skills, with a proven ability to convey complex scientific concepts to diverse audiences.

Preferred Experience and Skills:

• Expertise in utilizing network-based analysis frameworks to infer gene regulatory patterns and signaling pathways from next-generation sequencing (NGS) data, enabling the identification of potential therapeutic targets and conducting mechanism of action studies

• Familiarity with high-throughput siRNA/CRISPR/chemical screens in translationally-relevant preclinical models of immunological diseases

• Familiarity with animal models of immune-mediated diseases

• Familiarity with drug discovery across multiple modalities (e.g., small molecule, biologic, etc.)

Travel

• Up to 10% travel is required

Current Employees apply HERE

Current Contingent Workers apply HERE

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U.S. Hybrid Work Model

Effective September 5, 2023, employees in office-based positions in the U.S. will be working a Hybrid work consisting of three total days on-site per week, Monday - Thursday, although the specific days may vary by site or organization, with Friday designated as a remote-working day, unless business critical tasks require an on-site presence.This Hybrid work model does not apply to, and daily in-person attendance is required for, field-based positions; facility-based, manufacturing-based, or research-based positions where the work to be performed is located at a Company site; positions covered by a collective-bargaining agreement (unless the agreement provides for hybrid work); or any other position for which the Company has determined the job requirements cannot be reasonably met working remotely. Please note, this Hybrid work model guidance also does not apply to roles that have been designated as “remote”.

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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails. 

Employee Status:

Regular

Relocation:

Domestic

VISA Sponsorship:

Yes

Travel Requirements:

10%

Flexible Work Arrangements:

Hybrid

Shift:

Not Indicated

Valid Driving License:

No

Hazardous Material(s):

n/a

Job Posting End Date:

03/31/2025

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