SenNet Consortium Underrepresented Student Program Summer 2023 Application

2023 applications are now closed!

Sixteen SenNet labs are accepting interns in Summer 2023.

To apply, fill out the application form along with a personal statement and transcript. As part of the application process, students must also have 2 letters of recommendation sent to cusp@sennetconsortium.org . All materials are due by March 31, 2023.

Questions? Email cusp@sennetconsortium.org

Important Dates

Applications Open: January 15, 2023

Applications Close: March 31, 2023

Acceptance Notifications Sent Out: 

Performance Period: ~ 10-12 weeks between June 5 – August 18, 2023

Information for 2023 Applicants

Eligibility

Eligible students will:

  • Be an undergraduate student attending a US institution at the time of application.
  • Be college undergraduates in the United States majoring in any of the STEM fields with a minimum of 2.5 grade point average.
  • Be a member of an underrepresented group (as defined by NIH). See the NIH criteria.

Preference will be given to students who do not have ready access to biomedical (and/or single cell biology) research opportunities in their home institutions.

 

Application

All applicants will be required to submit an application form, transcript, personal statement, and 2 letters of recommendation. All materials should be submitted via the application form, by March 31, 2023.

Transcript: Unofficial transcripts are acceptable. Please submit transcripts as an attachment to your application form, as a PDF.

Personal Statement: Please submit a personal statement as an attachment to your application form, briefly describing your background, interest in participating in this summer undergraduate research program in single cell science, and your career goals. Please attach your personal statement in PDF format. Personal statements should be no longer than 2 pages single spaced, font size 11, Times New Roman.

Letters of recommendation: Two letters of recommendation should be sent to the application committee from your references, by the application due date of March 31, 2023. Letters of recommendation should be sent to cusp@sennetconsortium.org

Requirements & Expectations

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
  • At least a 2.5 GPA
  • A demonstrated strong work ethic
  • Some experience with lab work
  • A personal statement which outlines their interests and experience

 

Funding

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

2023 CUSP Program Opportunities

University of California San Diego

Projects in my lab will focus on validation of genetic and pharmacological approaches to eliminate senescent cells from mouse liver, brain, mammary, colon and bone marrow

Columbia University Irving Medical Center

CUIMC tissue mapping center is building an atlas of senescence in healthy individuals from 20-80 years old. The incoming student will learn the visium workflow generating spatial sequencing data from postmortem human tissue. The workflow includes sectioning of cortex/hippocampus, H&E staining, quality control and library preparation.

CUIMC tissue mapping center is building an atlas of senescence in healthy individuals from 20-80 years old. The incoming student will learn all the computational workflows involved in running spatial transcriptomics data including processing and quality control with Spaceranger, annotation using microscopy images through Loupe, and downstream statistical analysis using Splotch, a statistical model of spatial transcription.

Buck Institute for Research on Aging

Two potential projects- TMC (U54):
This project aims to identify, map and validate senescent cells in the human ovary and characterize cell types in the post-menopausal ovary. Trainees on this project will characterize the presence of canonical and novel senescence markers in human post-menopausal ovarian tissue using immunohistochemical and histological techniques. Then, using semi-quantitative analysis, they will map the distribution of markers in whole ovarian tissue sections across ages.

TDA (UG3):
This project is piloting the use of the microphysiologic ex vivo tissue-on-a-chip platform (LATTICE) to study cellular senescence beyond standard static cell culture methods. LATTICE provides a more physiologic platform for screening and evaluating senolytics/senostatics and SASP immune-depletion. Trainees on this project will examine expression of canonical and novel senescence markers in doxorubicin-induced cellular senescence in a standard tissue culture system versus doxorubicin-induced senescence in culture using microphysiologic ex vivo tissue-on-a-chip platform (LATTICE).

Pacific Northwest National Laboratory or subaward Oregon Health & Science University 

Our labs at the Pacific Northwest National Laboratory (PNNL) and Oregon Health & Science University (OHSU) are developing methods to identify and molecularly map senescent cells in tissues. We use a genetically-controlled, tamoxifen-inducible, senescent mouse model termed the FASST mouse to induce senescence stochastically in the stroma. One potential project for a CUSP trainee at OHSU would include histological characterization of FASST mouse tissue and would incorporate a variety of techniques including tissue isolation, embedding, fixation and immuno-histochemical staining. We are using the senescent tissue from this mouse to develop a spatial proteomics platform to characterize the senescence proteome and secretome. One potential CUSP project at PNNL would include proteomics characterization of FASST mouse tissue sections that would include laser microdissectioning, microfluidic sample preparation and liquid chromatography coupled with mass spectrometry.

Stanford University

Below are the couple of projects that will be feasible for the trainees during their time in our research group:
1. Immunohistochemistry of the pig knee sections to detect senescence.
2. Detecting senescence in human synoviocytes and chondrocytes derived from healthy individuals and those with osteoarthritis/rheumatoid arthritis using a novel radiotracer and validating it with conventional approaches.
3. Radiotracer based imaging of age-induced senescence across different healthy tissues in mouse models.

University of Minnesota – Bernlohr

The Midwest Mouse TMC invites students interested in summer internships in 2023 to consider opportunities to study cellular senescence within the context of adipose, muscle, lung, brain or liver biology. The MMTMC has opportunities to work alongside investigators assessing cellular senescence using state of the art omics technologies as applied to mouse models of aging. Work can either be focused on assessing protein or gene expression via a battery of technologies available to investigators as part of the MMTMC consortium.

University of Connecticut Health

1. Effects of senolytics (d+q) on beta cell function and gene identity using human islets from non-diabetic individuals
2. Relation between senescence on human pancreas vasculature and pancreatic islets
3. Morphometric distribution and analysis of pancreatic senescence using a p21cip-dTom mouse reporter model

Washington University

The Washington University Senescence Tissue Mapping Center (WU-SN-TMC) is developing cellular senescence atlases with a focus on human liver and bone marrow tissues across the lifespan.  

The candidate will work with an interdisciplinary team of investigators to support the construction of the cellular senescence atlases under investigation. Techniques learned may include tissue procurement and processing for high-dimensional genomics and proteomics analyses, computational analysis of multiple data types and/or validation of senescent biomarkers through in vitro cell and tissue culture experiments, depending on the interests of the candidate. The candidate will be and able to attend dynamic lab meetings and seminars and interact with graduate students, fellows, and senior scientists at an outstanding research environment.

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. Potential summer projects for students with programming experience include 1) development of a dashboard for visualization of complex data sets, 2) exploring the chromatin accessibly landscape of senescent cells across normal tissues, and 3) application of text mining methods to build a knowledge graph of senescent cell biology. The intern would be working with a team of faculty, staff, postdocs and graduate students with expertise in statistics and computational biology, and get to take part in our dry lab meetings and journal clubs.

Michigan University

University of Michigan SenNet TDA is working on developing and optimizing Seq-Scope for sensitive detection and characterization of senescent cells in tissues. Seq-Scope is a novel technology that enables microscopic examination of spatial transcriptome in diverse tissues. Potential summer projects include (1) application of Seq-Scope to different tissues undergoing senescence, (2) optimization of Seq-Scope for detecting senescent cells, and (3) developing new functionalities in Seq-Scope.

University of Minnesota -Niedernhofer

Looking for 1 CUSP student this summer who is interested in bioinformatics and 1 interested in wet bench research.

Bioinformatics: Modeling senescent cell behavior and impact in human liver.
Wet bench: Cross-validation of senescent cell biomarkers across multiple human tissues and technology platforms (spatial transcriptomics and proteomics).

Yale University – Dixit

Project available to study effects of aging on murine spleen, lymph node and thymus and identification of key biomarkers defining aging. Studies for summer 2023 include advanced imaging of tissues.

Yale University – Fan

Stephanie Halene
The study of cellular senescence in primary lymph tissues from younger and older human subjects.
Rong Fan
The Fan lab has developed novel omics methods to study spatial expression of proteins, mRNAs and the underlying epigenetic mechanisms related to aging.

The Ohio State University

The trainee will be receiving training in the laboratory of Dr. Mauricio Rojas and Ana L Mora at the Davis Heart Research Lung Institute. The student will work directly under the supervision of postdoctoral fellow Drs. Lorena Rosas and Natalia Vanegas, learning the preparation, in vitro culture and analyses of the novel technique of precision cut lung slices. Studies will characterize markers of senescence using different stimuli and time points in the distinct lung cell types.

University of Pittsburgh

The Koenigshoff lab 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 CUSP student will get 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 student will get trained and work together with two TriState SenNet Postdoctoral Fellows in the laboratory and integrated in our weekly SenNet meetings. 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.

Cornell University (Ithaca, NY)

This project will involve developing and testing computational approaches to identify cellular senescence in single-cell multi-omic datasets collected from various mouse tissues. The researcher will perform bioinformatic programming to handle single-cell RNA-sequencing datasets and map gene expression signatures on to them.

Mayo – NIA SenNet Mouse (Mayo Clinic, Rochester MN)

This project will involve establishment of the location and identity of senescent cells from the mouse spinal cord in the Baker laboratory. Techniques that will be learned include animal handling, histology, RNA isolation, and gene expression profiling.

Massachusetts Institute of Technology

1. Imaging mouse tissues using state-of-the-art Raman microscope.
2. Applying machine-learning algorithm to establish a connection between Raman and omics data.
Single-cell multi-omics profiling assays (e.g., single-cell RNA-seq, ATAC-seq, proteomics) have opened new windows into understanding the properties, regulation, dynamics, and function of senescence at unprecedented resolution and scale. However, these assays are inherently destructive, precluding us from tracking the molecular profiles and dynamics of live cells, in cell culture or whole organisms. We are developing an innovative technology, “SenNetRaman,” by 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. Interested students can join us at MIT and Massachusetts General Hospital/Harvard Medical School 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.