Oversee the analysis of high-dimensional datasets (e.g., scRNA-seq, CITE-seq, flow cytometry, and spatial transcriptomics) to identify pharmacodynamic markers and predictive signatures, to interpret ...
Oversee the analysis of high-dimensional datasets (e.g., scRNA-seq, CITE-seq, flow cytometry, and spatial transcriptomics) to identify pharmacodynamic markers and predictive signatures, to interpret ...
Experience with multiplex tissue-based spatial profiling assays (i.e., multiplex immunofluorescence, multiplex chromogenic immunohistochemistry, imaging mass cytometry, spatial transcriptomics)
Experience with multiplex tissue-based spatial profiling assays (i.e., multiplex immunofluorescence, multiplex chromogenic immunohistochemistry, imaging mass cytometry, spatial transcriptomics)
Experience with multiplex tissue-based spatial profiling assays (i.e., multiplex immunofluorescence, multiplex chromogenic immunohistochemistry, imaging mass cytometry, spatial transcriptomics)
Experience with multiplex tissue-based spatial profiling assays (i.e., multiplex immunofluorescence, multiplex chromogenic immunohistochemistry, imaging mass cytometry, spatial transcriptomics)
Bioinformatics - Assistant to Associate Professor, Non-Tenure Research Track
New Brunswick, NJ · On-site
$114K/yr
Spatial transcriptomics: Analysis and integration of spatially resolved gene expression data to characterize tissue architecture, cell-cell interactions, and microenvironmental heterogeneity. * Long ...
Bioinformatics - Assistant to Associate Professor, Non-Tenure Research Track
New Brunswick, NJ · On-site
$114K/yr
Spatial transcriptomics: Analysis and integration of spatially resolved gene expression data to characterize tissue architecture, cell-cell interactions, and microenvironmental heterogeneity. * Long ...
Associate Director, Translational Science
Somerset, NJ · On-site
$62K - $62K/yr
Oversee the analysis of high-dimensional datasets (e.g., scRNA-seq, CITE-seq, flow cytometry, and spatial transcriptomics) to identify pharmacodynamic markers and predictive signatures, to interpret ...
Associate Director, Translational Science
Somerset, NJ · On-site
$62K - $62K/yr
Oversee the analysis of high-dimensional datasets (e.g., scRNA-seq, CITE-seq, flow cytometry, and spatial transcriptomics) to identify pharmacodynamic markers and predictive signatures, to interpret ...
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics, and biomarker endpoints to pharmaceutical and biotechnology sponsors. Our team is scientifically ...
We deliver anatomic histopathology, immunostaining, digital image analysis, spatial transcriptomics, and biomarker endpoints to pharmaceutical and biotechnology sponsors. Our team is scientifically ...
Spatial Transcriptomics information
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.
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 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 popular job titles related to Spatial Transcriptomics jobs in New Jersey? For Spatial Transcriptomics jobs in New Jersey, the most frequently searched job titles are:
- Senior Computational Biologist
- Freelance Protein Engineering Scientist
- Senior Bioinformatics Scientist
- Computational Chemistry Molecular Modeling
- Internship Pk Pd Scientist
- Principal Scientist Immunology
- Flex Next Generation Sequencing Scientist
- Computational Scientist Remote
- Variant Scientist
- Phd Data Scientist
What job categories do people searching Spatial Transcriptomics jobs in New Jersey look for? The top searched job categories for Spatial Transcriptomics jobs in New Jersey are:
What cities in New Jersey are hiring for Spatial Transcriptomics jobs? Cities in New Jersey with the most Spatial Transcriptomics job openings:
Other
Posted 15 days ago
Job description
Legend Biotech is seeking an Associate Director, Translational Science as part of the Early Drug Development team based in Somerset, NJ.
Role Overview
The Associate Director of Translational Science will bridge the gap between early-stage discovery research and clinical development. This role requires a unique blend of deep immunological expertise and advanced computational proficiency. You will be responsible for designing and executing translational strategies, identifying biomarkers, and leveraging large-scale multi-omic datasets to provide actionable insights into mechanism of action (MoA), patient stratification, and drug resistance in both autoimmune and oncology disease area.
Key Responsibilities
- Translational Strategy: Lead the development and execution of program-specific translational plans from lead optimization through Phase II clinical trials.
- Data Integration & Analysis: Oversee the analysis of high-dimensional datasets (e.g., scRNA-seq, CITE-seq, flow cytometry, and spatial transcriptomics) to identify pharmacodynamic markers and predictive signatures, to interpret and provide insight into the biological mechanisms.
- Clinical Collaboration: Partner with Clinical Development and Clinical Operations to implement biomarker assays in clinical protocols and ensure high-quality data collection.
- External Partnerships: Manage relationships with Contract Research Organizations (CROs) and academic collaborators for specialized assay development and advanced data processing.
- Cross-Functional Leadership: Represent Translational Science on program teams, providing expert input on disease biology, target engagement, and competitive landscape.
- Scientific Communication: Author high-quality technical reports, regulatory documents (IND/IB/NDA), and contribute to peer-reviewed publications and conference presentations.
Requirements
- PhD or MD/PhD in Immunology, Bioinformatics, Computational Biology, or a related field.
- 5+ years of experience in the biopharmaceutical industry or an equivalent academic leadership role within translational research.
- Extensive knowledge of human auto-immune disease and oncology diseases, specifically in areas such as immuno-oncology, autoimmune diseases, or cell therapy (CAR-T/TCR-T).
- Demonstrated experience with genomic data analysis. Practical and hand on experience data analysis pipeline, ability to guide data integration, knowledge integration from multiple datasets is essential.
- Proven track record in the development, validation, and clinical implementation of complex biomarkers.
- Experience working with relevant disease areas, deep understanding of the biological mechanisms related to diseases(auto-immune, oncology, or/both).
- Strong understanding of regulatory requirements for biomarker-driven clinical trials.
- Excellent project management skills with the ability to lead multiple programs in a fast-paced environment.
- High scientific curiosity, driven, motivated in deep understanding of the biology behind both disease and therapies.
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