Data Scientist – Spatial Transcriptomics-Remote(India)

Job Title: Data Scientist Spatial Transcriptomics

Location: Remote PAN India (Hyderabad preferred)

Employment Type: Contract (12 Months)

Experience: Relevant research experience in computational biology and spatial transcriptomics

Total Years of experience needed- 8 + years

Working Hours: 9:00 AM 6:00 PM IST, with occasional U.S. collaboration meetings between 7:00 PM and 10:00 PM IST.

Notice period-Immediate-30 days

Job Summary

We are looking for a research-oriented Data Scientist with a relevant PhD and hands-on experience in spatial transcriptomics and computational analysis of biological datasets. The ideal candidate will combine strong computational biology expertise with an understanding of biological sample processing, experimental data generation, and biological interpretation.

This role requires practical research experience in analyzing spatial transcriptomics and single-cell datasets, developing reproducible analytical workflows, and translating complex biological data into meaningful scientific insights.

Key Responsibilities

• Perform quality control and preprocessing of spatial transcriptomics and single-cell datasets, including filtering, doublet detection, and contamination assessment.
• Conduct data normalization, integration, dimensionality reduction (PCA, UMAP, t-SNE), clustering, and cell-type annotation.
• Perform differential expression analysis, pathway enrichment, trajectory inference, pseudotime analysis, and gene regulatory network analysis.
• Analyze spatial gene expression patterns, identify spatial domains, map cell populations, and perform cell-type deconvolution and neighborhood analysis.
• Integrate spatial transcriptomics with single-cell RNA sequencing and other relevant multimodal datasets, including scATAC-seq and Multiome data where applicable.
• Develop and maintain reproducible computational pipelines and document analytical methods, results, and workflows.
• Interpret results in the context of biological research questions and communicate findings through scientific reports, presentations, and discussions.
• Collaborate with experimental scientists and cross-functional research teams to connect computational findings with biological observations.

Required Qualifications

• PhD in Computational Biology, Bioinformatics, Genomics, Biology, Biotechnology, or a closely related discipline.
• Hands-on experience in spatial transcriptomics data analysis is essential.
• Demonstrated experience analyzing biological research datasets and interpreting results in a scientific context.
• Strong understanding of single-cell RNA sequencing and relevant computational biology methods.
• Experience with tools and programming languages such as R and/or Python, along with relevant packages such as Seurat, Scanpy, or Bioconductor.
• Understanding of biological sample processing and experimental data-generation workflows.
• Ability to independently manage analytical tasks, troubleshoot data challenges, and explain scientific findings clearly.
• Experience working with Linux environments, HPC, or cloud-based analytical workflows is an advantage.

Preferred Qualifications

• Experience with 10x Genomics Visium or comparable spatial transcriptomics platforms.
• Experience integrating spatial transcriptomics with scRNA-seq datasets.
• Familiarity with spatial analysis tools and methods for spatial domain identification, deconvolution, and cell-neighborhood analysis.
• Experience with reproducible workflows, pipeline automation, and large-scale biological datasets.

Work Arrangement

• Remote opportunity open to candidates across India; Hyderabad-based candidates preferred.
• Standard working hours are 9:00 AM 6:00 PM IST.
• Occasional U.S.-team collaboration meetings may be scheduled between 7:00 PM and 10:00 PM IST, generally once a week for approximately two hours, with suitable adjustment to the work schedule.

Important: Candidates must have practical spatial transcriptomics research experience. A background limited to general bioinformatics, bulk RNA-seq, or software development without hands-on spatial transcriptomics analysis will not be sufficient.

Follow us to get more job updates: https://www.linkedin.com/company/hyr-global-source-inc