Discovery Postdoctoral Fellow, Spatial Transcriptomics - Neuroscience

About the role

The Novartis Biomedical Research Postdoctoral Fellowship Program offers a unique training opportunity for early-career scientists to tackle significant challenges in biomedical research and drug discovery. As a Discovery Postdoctoral Fellow, you will join Neuroscience in Cambridge and conduct innovative research on novel therapeutic targets for amyotrophic lateral sclerosis (ALS) at the neuroimmune interface.

Responsibilities

• Establish and apply high-resolution spatial transcriptomics workflows to profile disease-relevant regions in ALS model systems and identify spatially organized gene-expression programs.
• Develop and benchmark computational pipelines for spatial transcriptomic analysis, including spatial clustering, gene-module detection, ligand–receptor interaction mapping, and integration with single-cell and human ALS datasets.
• Generate and characterize CRISPR-engineered knockout or knock-in human iPSC lines for selected spatially identified target genes.
• Collaborate closely with multidisciplinary teams across neuroscience, functional genomics, bioinformatics, genome engineering, stem cell biology, and translational research.
• Communicate research findings through internal presentations, conference abstracts, and peer-reviewed publications.

Requirements

• PhD (or equivalent doctoral degree) in neuroscience, biology or related discipline (completed prior to the fellowship start date).
• Demonstrated record of scientific achievement (publications, presentations, patents, or equivalent).
• Strong commitment to learning, innovation, and professional development.
• Strong background in spatial transcriptomics, single-cell genomics, stem cell biology, functional genomics, or related areas.
• Experience with human iPSC-derived cell lines and models.
• Demonstrated ability to analyze complex omics datasets.

Desirable Requirements

• Hands-on experience with one or more relevant experimental platforms, such as tissue processing, transcriptomic profiling, human iPSC culture and differentiation, CRISPR/Cas9 genome editing, high-content imaging, co-culture systems, or functional cellular assays.
• Familiarity with computational analysis of transcriptomic or spatial omics datasets, including use of tools or workflows such as Seurat, spatial clustering, differential gene-expression analysis, pathway analysis, or cell–cell communication analysis.