Accepted students are required to:

• -Conduct your own small research project or work on part of an ongoing research project.
• -Attend a weekly virtual seminar series that will introduce you to rapidly progressing medical and basic research areas.
• -Complete all Compliance Training, Conflict of Interest Forms and/or any other training deemed necessary for your internship as soon as it is received.
• -Report to work on time as designated by the mentor to work on assigned research project. Students are expected to work no more than 40 hours a week.
• -Present a virtual poster at the end of the project about your experience. The date of the presentation will be determined by the NIH SenNet program.

Successful applicants will have:

-An interest in and passion for studying biological or computational sciences, or related STEM fields
-A demonstrated strong work ethic
-Some experience with lab work

Funding:

Accepted students will receive a stipend, housing, travel, and technology assistance as needed.

Carnegie Mellon University

The Carnegie Mellon University research group aims to develop and implement the next generation of computational methods to perform learning, inference, and decision-making on biomedical and healthcare data for accelerating scientific knowledge discovery and generating confident and testable data-driven hypotheses.

The research group applies these methods to answer important scientific questions as well as emerging high-impact real-world problems. Examples include elucidating the molecular mechanisms underlying human genetic diseases as well as identifying the spatial organization of senescent cells, the identification of their neighboring cells and the identification of novel genes involved in cell-cell interactions that may be driving senescence.

The candidate will report to Dr. Jose Lugo-Martinez. 

Columbia University Irving Medical Center

The Columbia University Senescence Tissue Mapping Center is in the heart of Upper Manhattan in New York City. The focus of the CUSTMAP center is to create a multi-scale atlas of senescence in diverse tissue types across human life span. Using spatial transcriptomics, experimental workflows and analytical pipelines, CUSTMAP aims to generate three dimensional maps of how cells senesce in tissues of central nervous system: prefrontal dorsolateral cortex, hippocampus and spinal cord.

The student will be expected to assist with tissue processing, which includes but is not limited to cryosectioning, hematoxylin and eosin staining, imaging of the tissue, and tracking the metadata. The student will also perform quality control on copyDNA, all final libraries, and will help with manual annotation of the tissue for downstream computational analysis.

The candidate’s preferred skills would be one or more years’ experience of bench work in molecular biology methods, some exposure to microscopy and ability to clearly communicate verbally and in writing. The candidate will report to Dr. Phatnani.

Columbia University (Dept. of Dermatology)

The Columbia University Department of Dermatology focuses on modeling intrinsic and extrinsic senescence in vitro using complex bioengineered human tissues, with a particular focus skin and adipose tissue. Their current TDA project is called “Senescence-on-a-chip: Building a microphysiological 3D skin model.”

The site investigates the expression and distribution of known and unknown senescence markers applying spatial proteomics and spatial transcriptomics assays in three-dimensional skin constructs and adipose tissue constructs.

The candidate will have the opportunity to learn the basis of tissue engineering, and how to perform basic and advanced assays, including simple and multiplexed immunostainings and ELISA, and spatial transcriptomics. Previous experience with cell culture and/or with common laboratory assays is preferred.

Duke University

The Duke University SenNet Tissue Mapping Center is developing novel statistical and computational methods for the analysis of single cell and spatial transcriptomics data sets from lung and colon samples.

If the candidate has programming experience, they may participate in development of a dashboard for visualization of complex data sets, exploring the chromatin accessibly landscape of senescent cells across normal tissues, or in the application of text mining methods to build a knowledge graph of senescent cell biology.

The candidate will be working with a team of faculty, staff, postdocs and graduate students with expertise in statistics and computational biology and will get to take part in our dry lab meetings and journal clubs. The candidate would Dr. Jason Ji and interact with other members of the Data Analysis Core.

Duke University (Wang Lab)

The Wang Lab at Duke University Medical Center is located on the second floor of the Levine Science Research Center (LSRC). The LSRC building hosts multidisciplinary laboratories and requisite support facilities spanning basic research and clinical departments focused on cancer, neuroscience, and computer science.

The Wang lab occupies approximately 2,000 square feet of space, plus adjacent three shared equipment rooms and a medium-sized cold room. Currently, the lab is dedicated to exploring molecular mechanisms underlying cellular senescence and age-related diseases with the objective of developing senolytic-based therapeutics (Further details about the lab’s work can be found on the lab website: https://www.xfwanglab.com/).

The candidate will actively investigate the role of senescence-related molecular mechanisms in the onset of neurodegenerative diseases, such as Alzheimer’s disease. The candidate should have adequate knowledge of cell biology and molecular biology principles. Previous experience in cell culture and basic molecular biology experiments will be advantageous. The candidate will report directly to Dr. Xiao-Fan Wang.

The Jackson Laboratory

The Jackson Laboratory in Farmington, CT focuses on spatial mapping of senescent cells, determining their biomarkers, and their interactions with neighboring cells. The lab features a dry lab space with access to local HPC.

The candidate will learn about spatial transcriptome data processing and analysis using Seurat, deep learning software designed to integrate the H&E image and spatial transcriptome. The candidate should have experience with R or Python and familiarity with bioinformatics. The candidate will report directly to Sheng Li, PhD.

Mayo Clinic (Rochester, MN)

The Baker laboratory of Mayo Clinic in Rochester, Minnesota focuses on identifying and characterizing senescent cells in the spinal cords of mice over aging and in conditions of pathology.

The candidate will have the opportunity to engage with our collaborative team from Johns Hopkins, the National Institute for Aging, and Cornell University. The candidate should be motivated, curious, and have a willingness to work closely with scientists across multiple research sites.

MIT

The MIT and Massachusetts General Hospital/Harvard Medical School research sites focus on single-cell multi-omics profiling assays (e.g., single-cell RNA-seq, ATAC-seq, proteomics) and how they can help researchers understand the properties, regulation, dynamics, and function of senescence at unprecedented resolution and scale. These assays are inherently destructive, precluding researchers from tracking the molecular profiles and dynamics of live cells, in cell culture or whole organisms.

As a solution, these sites are developing “SenNetRaman” through combining the recent advance in high-resolution Raman microscopy and single-cell and spatial multi-omics to unbiasedly map the molecular and cellular heterogeneity and spatial information of senescent cells non-destructively.

The candidate will join Prof. Peter So and Prof. Jian Shu at these sites to build a novel high throughput Raman microscope for developing unique deep-learning algorithms that allow prediction of multi-omics data from Raman spectra, and applying these technologies to identify senescence cells in young and old mouse lung specimens.

Mount Sinai

The research site at Mount Sinai focuses on lung- and endothelial-targeting of senescence molecules, including humanized mouse models of senescence. This involves exploring the dynamic interplay between molecular senescence pathways and the intricate physiology of these models.

The candidate will participate in learning experiences at the forefront of senescence research, specifically through conducting senescence-related enzyme activity analysis in human tissue to elucidate senescence patterns in the lungs.

Ohio State University

The Davis Heart Research Lung Institute at Ohio State University focuses on the preparation, in vitro culture, and analyses of the novel technique of precision cut lung slices. Studies characterize markers of senescence using different stimuli and time points in the distinct lung cell types.

The candidate will receive training in the laboratory of Dr. Mauricio Rojas and Ana L. Mora and will work directly under the supervision of postdoctoral fellows Drs. Lorena Rosas and Natalia Vanegas. The candidate will also be integrated into our weekly SenNet meetings.

Pacific Northwest National Laboratory

The Pacific Northwest National Laboratory (PNNL) and Oregon Health & Science University (OHSU) in Portland, OR focus on identifying and molecularly mapping senescent cells in tissues. The site uses a genetically-controlled, tamoxifen-inducible, senescent mouse model termed the FASST mouse to induce senescence stochastically in the stroma.

The candidate at OHSU will work with histological characterization of FASST mouse tissue and would incorporate a variety of techniques including tissue isolation, embedding, fixation and immuno-histochemical staining. PNNL uses the senescent tissue from this mouse to develop a single cell proteomics platform to characterize the senescence secretome.

The candidate will work with and report to Dr. Megan Ruhland at OHSU.

University of California San Diego

The University of California San Diego research site processes mouse tissues and performs targeted assays for presence and absence of senescent cells, e.g., immunofluorescence, immunohistochemistry, qPCR, RNA-scope.

The candidate will assist and/or shadow as appropriate during the application of the major data generation platforms, single cell sequencing, MERFISH and CODEX.

University of Michigan

The University of Michigan research site, located in Ann Arbor, MI, focuses on technology development and applications related to Seq-Scope, which can produce high-resolution spatial transcriptomics datasets.

For further specific information about research performed at this site, please visit their website (https://lee.lab.medicine.umich.edu/).

The candidate will report to the PI, along with the lab supervisor (grad student or postdoc) who will be assigned to the student. A background in molecular biology and biochemistry is preferred, but not required.

University of Minnesota (2 positions)

The University of Minnesota Tissue Mapping Center (MN TMC) is focused on mapping senescent cells within human adipose and liver tissues. The candidate will be involved in spatial and single cell techniques to characterize senescence and learn aging biology research techniques in Dr. Laura Niedernhofer’s lab at the University of Minnesota.

The Midwest Murine Tissue Mapping Center (MM TMC) is focused on mapping senescent cells within mouse adipose, brain, liver, muscle and lung tissues. Adipose, liver and brain tissue research is conducted at the University of Minnesota, muscle research is conducted at Mayo Clinic, Rochester, and lung research is conducted at Northwestern University. The candidate will be involved in spatial and single cell techniques to characterize senescence and learn aging biology research techniques.

University of Pittsburgh

The Koenigshoff lab at the University of Pittsburgh is focused on deciphering mechanisms involved in lung aging and regeneration, with the aim of identifying novel therapeutic targets relevant for age-related chronic lung diseases, such as idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD).

The Koenigshoff lab is composed of a multi-disciplinary group of people from different backgrounds and cultures with the guiding principle that diverse viewpoints and perspectives will lead to more creative and innovative, and thus better, science.

The candidate will be introduced to human tissue-derived models of lung aging and analyze senescence associated proteins. Major methodologies include cell and tissue culture as well as molecular biological analysis techniques. The candidate will work together with two TriState SenNet Postdoctoral Fellows in the laboratory and be integrated into our weekly SenNet meetings.

University of Washington

The University of Washington (Seattle) research site develops Pixel-seq, an integrative spatial transcriptomic and proteomic assay using ≤1-µm-resolution polony gels for spatial barcoding and sequencing. Researchers use Pixel-seq to spatially map ‘omics’ states of diverse cell types in morphologically intact mouse and human tissues across the lifespan to identify senescent cells and biomarkers. Researchers also employ high-throughput protein engineering, polony gel fabrication and sequencing, mass spectrometry, and fluorescence imaging.

The candidate should have a background in related fields such as biochemistry, genetics, bioengineering, immunology, and neuroscience, will receive experimental and computational training, and will learn how to generate single-cell-resolution maps of any chosen tissue type to detect senescent cells. The project is led by Liangcai Gu, Associate Professor of Biochemistry.

Yale University (2 positions)

Yale University has two Tissue Mapping Centers (TMCs), both working on mapping senescent cells in primary and secondary lymphoid organs to improve our understanding of cellular senescence in development, aging and disease (https://medicine.yale.edu/pathology/research/sennet/).

The Human TMC, led by Drs. Rong Fan and Stephanie Halene, focuses on characterizing primary lymph tissues from younger and older human subjects. The Murine TMC, under the direction of Drs. Vishwa Deep Dixit and Ruth Montgomery, focuses on murine models to characterize senescent cells in spleen, lymph node, and thymus. Both programs utilize high-throughput, high-resolution single cell and spatial omics technologies to characterize senescent cell heterogeneity.

The candidates will be co-advised by two laboratories within the Yale TMCs, and co-trained on relevant benchwork, as well as on computational analysis. The candidates will participate in laboratory meetings and in the monthly joint meeting of both TMCs. The candidates will characterize senescent cell markers in lymphoid organs from younger and older humans or mice using a variety of techniques such as immunohistochemistry, DBiT-seq, and spatial omics (PhenoCycler), and learn how to computationally analyze the data from these assays. The candidates should have a basic knowledge of molecular biology and immunology.

Ten simple rules for students navigating summer research experiences for undergraduates (REU) programs: from application to program completion.