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Spatial Transcriptomics Jobs in Indiana (NOW HIRING)

Spatial Transcriptomics information

What are the key skills and qualifications needed to thrive as a Spatial Transcriptomics Scientist, and why are they important?

To thrive as a Spatial Transcriptomics Scientist, you need a strong background in molecular biology, genomics, and bioinformatics, typically supported by an advanced degree in a life science field. Familiarity with spatial transcriptomics platforms (such as 10x Genomics Visium), next-generation sequencing (NGS) technologies, and data analysis tools like R or Python is essential. Strong problem-solving skills, attention to detail, and effective communication are important soft skills for collaborating on interdisciplinary research projects. These skills and qualities are crucial for generating high-quality spatial gene expression data and translating findings into meaningful biological insights.

What are some common challenges faced by professionals working in spatial transcriptomics, and how can they be addressed?

Professionals in spatial transcriptomics often encounter challenges related to handling large, complex datasets and integrating spatial information with gene expression data. Ensuring high-quality sample preparation and mastering advanced imaging or sequencing technologies are also frequent hurdles. These challenges can be addressed by collaborating closely with multidisciplinary teams—including bioinformaticians, molecular biologists, and imaging specialists—and staying up-to-date with the latest software tools and protocols. Continuous learning and effective communication within the team are key to overcoming technical and analytical obstacles in this rapidly evolving field.

What is spatial transcriptomics?

Spatial transcriptomics is an advanced technique that allows scientists to measure gene expression within the spatial context of tissue samples. Unlike traditional RNA sequencing, which loses information about where each gene is expressed, spatial transcriptomics preserves the physical location of gene activity in tissues. This helps researchers better understand how cells function within their native environments and interact with neighboring cells, which is especially valuable in fields like cancer research, neuroscience, and developmental biology. The method combines microscopy, molecular biology, and computational analysis to produce detailed maps of gene expression.
Postdoctoral Fellow in Pediatrics

Postdoctoral Fellow in Pediatrics

Indiana University

Bloomington, IN • On-site

$45.30K - $61.50K/yr

Full-time

Posted 12 days ago


Job description

Posting Details
Position Details
Title
Postdoctoral Fellow in Pediatrics
Specific Title
Appointment Type
Postdoctoral Fellow
Department
IUSM - Pediatrics
Campus
IU School of Medicine Indianapolis
Position Summary
The Schwaderer Lab is dedicated to uncovering the biological mechanisms underlying kidney diseases, particularly those with immune-mediated components such as kidney infections, kidney stones, and glomerular disorders. Our research integrates cutting-edge approaches to understand how immune responses contribute to kidney injury and disease progression.
In addition, we focus on biomarker discovery to identify children at risk for developing kidney disease and to guide personalized treatment strategies. By leveraging advanced technologies in genomics, proteomics, and metabolomics, our goal is to improve early detection, predict disease outcomes, and develop targeted interventions that enhance patient care and long-term kidney health.
Bioinformatics and Biomarker Analysis in Kidney Disease The Nephrology and Urology Research Group at Indiana University School of Medicine seeks a highly motivated individual to join our team in advancing the understanding of kidney disease through cutting-edge bioinformatics and biomarker research. This position focuses on the integration and analysis of complex biological data to identify and validate kidney disease biomarkers. Research Focus Our program leverages multi-omics platforms (including proteomics, metabolomics, transcriptomics), targeted biomarker arrays, and advanced computational approaches to:
Characterize biomarker profiles across kidney tissue, serum, urine, and other biological samples. Integrate multi-modal datasets to uncover mechanisms underlying kidney disease progression and treatment response. Apply advanced microscopy image analysis and spatial transcriptomics to link molecular signatures with tissue architecture. Develop predictive models for disease diagnosis, prognosis, and therapeutic targeting.
Experimental and Analytical Approaches
Bioinformatics and computational biology for multi-omics integration and biomarker discovery. High-dimensional data analysis from targeted arrays and imaging platforms. Coordination of biological sample pipelines (kidney biopsy, serum, urine) for comprehensive biomarker profiling. Utilization of machine learning and image processing for advanced tissue analysis.
The Herman B Wells Center for Pediatric Research conducts basic science and translational research within the Department of Pediatrics at Indiana University School of Medicine. The Wells Center houses more than 300 faculty investigators, staff, and trainees seeking answers to the most pressing questions related to childhood illness. With the collaboration between scientists and physicians, the center aims to increase knowledge of causes and mechanisms of serious pediatric diseases. Our goal is to develop innovative approaches to the diagnosis and treatment of sick children in Indiana and beyond.
IUSM is committed to being a welcoming campus community and we seek candidates whose research, teaching, and community engagement efforts contribute to robust learning and working environments for all students, staff, and faculty. We invite individuals who will join us in our mission to improve health equity and well-being for all throughout the state of Indiana.
Basic Qualifications
PhD in bioinformatics, molecular biology, nephrology, urology, or a related field
Department Contact for Questions
Andrew Schwaderer, MD
schwadea@iu.edu
Additional Qualifications
Preferred Qualifications
Experience in bioinformatics, computational biology, or related fields. Familiarity with omics data analysis, biostatistics, and image analysis tools. Strong programming skills (R, Python) and knowledge of relevant databases and pipelines. Candidates with peer-reviewed publications, excellent communication skills, and collaborative mindset will be prioritized.
Collaborative Environment The successful candidate will join a multidisciplinary team with expertise in nephrology, urology, molecular biology, and computational science. Access to patient samples, state-of-the-art imaging facilities, and high-performance computing resources will support translational research aimed at improving kidney health.
Special Instructions
Priority Application Review Deadline
Expected Start Date
Posting Number
IUSM-02341-2026