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University research directory
Research labs at
University of Pennsylvania.
Compare 5 listed faculty-led profiles, explore their research interests, and follow the evidence in their selected work. These listings are a starting point for discovery and do not establish recruiting availability.
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Review each lab’s official website and recent publications. Compare the methods used, the questions being asked, and the practical requirements of any published opening. Unclaimed profiles are independently curated; the university has not approved or endorsed them.
How to compare research labs ↗Official university website ↗5 research-led lab profiles
Browse labs by their listed college affiliationArjun Raj Research Group
University of PennsylvaniaArjun Raj · Professor of Bioengineering
How do genetically identical cells adopt different molecular fates within tissues and tumors? The Raj lab studies the biology of single cells using measurements of individual RNA molecules via fluorescence microscopy and high throughput sequencing. The group develops and utilizes experimental tools including fluorescence microscopy and sequencing to make quantitative measurements of cellular behavior. Researchers apply computational image analysis and machine learning to enable accurate spot detection and accelerate analysis of microscopy and sequencing data. The lab investigates how rare cells and multicellular organization drive outcomes like drug resistance and self-organization in cancer.
Carl H. June, M.D. Research Group
University of PennsylvaniaCarl H. June, M.D. · Richard W. Vague Professor in Immunotherapy
Can engineered T cells be reprogrammed to eliminate cancer while maintaining patient safety? The June Lab focuses on ex vivo T-cell engineering to create cell-based therapies for cancer and HIV. The laboratory is primarily responsible for developing new CARs and new vectors for current and proposed indications and for translating laboratory insights into clinical trials. Researchers apply genetic engineering and vector design to produce CAR T cells and related cellular immunotherapies for clinical testing. The lab integrates translational research to move biologically-focused ideas into safe, effective cancer therapies.
Independently curated · UnclaimedComplex Systems Lab
University of PennsylvaniaDani Smith Bassett · J. Peter Skirkanich Professor, University of Pennsylvania
What can the pattern of connections tell us about how a brain learns or changes state? Dani Smith Bassett’s Complex Systems Lab uses network science, mathematical modeling, and neuroimaging to investigate that question. Its research treats interactions among brain regions as a system whose architecture shapes its dynamics. Selected work includes a framework for network neuroscience and an MRI study of connectivity and blood-flow changes during sedation and recovery of consciousness. The lab connects physics, engineering, and neuroscience, giving newcomers a concrete starting point for studying how structure and activity relate across the brain.
Independently curated · UnclaimedReto Gieré Research Group
University of PennsylvaniaReto Gieré · Professor
How do minerals and urban particulates influence environmental health and human exposure? The Gieré lab investigates environmental geochemistry, mineralogy, and the health impacts of atmospheric pollution. Researchers characterize microplastics, road dust, and particulate matter using techniques such as XRD, ICP-OES, and SEM to determine composition and potential exposure pathways. The group applies geochemical modeling and microscopy to study contaminants in soils and urban media to inform remediation and exposure assessment. The lab participates in Penn centers focused on environmental toxicology to connect geochemical findings with public health questions.
Yoseph Barash Research Group
University of PennsylvaniaYoseph Barash · Professor of Genetics
How do sequence features and cellular context determine mechanisms of alternative splicing and post‑transcriptional isoform regulation in human tissues? The lab develops machine learning algorithms that integrate high‑throughput data such as RNASeq and CLIPSeq to infer RNA biogenesis and function. They build probabilistic graphical models and other computational methods to predict effects of genetic variation on RNA processing, including splicing QTLs. Predictions from computational models are followed by experimental verifications using high‑throughput sequencing assays to test inferred regulatory mechanisms. Ongoing projects include integrating long‑read 3′ and 5′ assays and polyA site annotation to resolve isoform diversity and variant effects on transcript ends.
Showing 1–5 of 5 labs