Underrepresented Student Internship Program

 

The Underrepresented Student Internship Program provides the opportunity for undergraduate students from US colleges and universities to receive mentorship and training from NIH Human Biomolecular Atlas Program (HuBMAP) labs over the summer.

Internship applications for 2022 have now closed.

Apply for an immersive research experience at one of our HuBMAP labs working at the cutting edge of single cell biology on experimental or computational projects and gain valuable research experience. This program is ideal for students in STEM fields, especially those interested in biology, data science, and medicine.

We are excited to offer both remote and in-person internships for 2022, offering flexibility to students.

Benefits of the HuBMAP summer internship

Learn valuable new skills across the scientific research spectrum and gain experience in an educational lab environment. During the internship program, students will conduct cutting-edge research, greatly expanding their knowledge of biology and data analysis. Students will develop a variety of skills throughout the summer, preparing them for future research endeavors. These include:

  • Learning GitHub, Python, JavaScript, other coding languages - especially for those students that pursue a computational internship experience
  • Working with lab techniques and technologies, such as sample preparation, pipetting, and analysis - especially for those students that pursue an experimental lab experience
  • Developing knowledge of spatial transcriptomics, 3D imaging, visualization, and data analysis
  • Learning skills that are applicable to all sciences and even other fields, such as reading publications, giving scientific presentations, resume writing, and conducting journal reviews
According to one of our 2021 interns, “The most exciting thing about the HuBMAP internship is that you can combine science and technology to create something that will contribute to the biotech community.” Apply today for a chance to be part of this exciting program!

Work with HuBMAP researchers and add to your resume!

See the research accomplished by our 2021 interns and read about their experiences

Questions? Email internshipapply@hubmapconsortium.org

 

Information for 2022 applicants:

  • In the lab descriptions below, we identify which experiences would be computational, and which would be experimental
  • Students can indicate on their application their preference for computational or experimental internships
  • Experimental internships will take place only in person, as permitted by the ongoing circumstances of the COVID-19 pandemic
  • Computational internships are offered either in person or virtually, to be determined in consultation with the hosting lab
  • Remote experiences will include virtual meetings and engagement activities to maintain a robust learning experience
  • In-person experiences will include assistance with housing and travel arrangements, and additional funding will be provided on a lab-by-lab basis
  • Due to the ongoing uncertainty of the COVID-19 pandemic, in-person experiences are not guaranteed. Furthermore, indicating “experimental” as a preference on one’s application does not guarantee a placement in an in-person lab experience, if accepted into the internship program.
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 3.0 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 February 18, 2022.

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 February 18, 2022. Letters of recommendation should be sent to internshipapply@hubmapconsortium.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 HuBMAP program .
Funding:

Accepted students will receive a stipend of $6,000. Additional funding to cover living and travel expenses for in-person experiences will be determined on a lab by lab basis.

Available Programs:

Thirteen HuBMAP labs will be hosting interns in summer 2022. Each description indicates if the lab is experimental or computational. Experimental labs offer in-person experiences, while computational labs offer either in-person or virtual experiences, to be determined in partnership with each lab. Read on for more information about each.
 
Gehlenborg Lab, Harvard Medical School (Computational)
The Gehlenborg Lab in the Department of Biomedical Informatics at Harvard Medical School is a group of data scientists and software developers who are passionate about driving biomedical discovery by creating efficient and effective visual interfaces between analysts and data. For the Summer of 2022 we are hoping to recruit a student to work on a project that will make HuBMAP data more accessible to the community, such as:
  • Develop or extend R and/or Python packages to interface with the HuBMAP Portal APIs to enable direct access in RStudio or Jupyter Notebooks
  • Create example visualizations with Vitessce (http://vitessce.io) that explain single-cell and tissue biology to lay audiences
  • Contribute new visualization types to Vitessce, e.g., interactive statistical graphs or specialized visualizations for HuBMAP data types
  • Extend the diversity data summary page developed by our 2021 HuBMAP Diversity Summer Intern: https://portal.hubmapconsortium.org/diversity
  • Projects that make communicating biomedical discoveries from single cell biology easier for lay audiences by exploring different visualizations, design principles etc.

Some previous experience with programming and software engineering will be useful in most projects but is not essential. An interest and experience in data visualization and visual design would be desirable but not required. However, we would also welcome students with more extensive background and experience in programming with R, Python or Javascript.

Lab Website


 
The Cyberinfrastructure for Network Science Center, Indiana University (Computational)
Our mission is to advance datasets, tools, and services for the study of biomedical, social and behavioral science, physics, and other networks. A specific focus is research on the structure and evolution of science and technology (S&T) and the communication of results via static and interactive maps of science (learn more at scimaps.org).

We develop custom interactive data visualization applications for both public and private sector clients in need of innovative ways to interpret and utilize their data.

As part of the HuBMAP HIVE Mapping Component at Indiana University, this lab welcomes applications by undergraduate students with a strong background in biology to work on the construction and usage of a Human Reference Atlas, see this article. Specifically, the student will work on data visualizations of anatomy and single-cell data in close collaboration with visualization experts and in the context of HuBMAP.

Qualifications:

  • Demonstrated strong data visualization expertise is required.
  • Have a basic knowledge in human anatomy, histology, or biomedical field.
  • Experience with vector image editing software, such as Adobe Illustrator and Inkscape.
  • Experience in cross-disciplinary teams and strong collaboration skills
  • A can-do work ethic

Lab Website

 
New York Genome Center (Computational)
This lab develops tools for the analysis and integration of sequencing datasets. We have a particular interest in applying these technologies to study single cells, a field known as single cell genomics, and utilizing this to better understand human biology. In HuBMAP, we are working on building reference maps of healthy human tissues, and generating a 'parts list' of the individual components that comprise a human being.

Students will receive introductory training in the R programming language, as well as introductory techniques for analyzing single-cell genomics research. They will conduct a research project working with closely with lab members to construct and update a reference map for one of the tissues in the HuBMAP project, such as the lung, kidney, or skin.

Prerequisites: Students should have an interest in pursuing a career in research, and in applying to graduate a program in Biology, Computational Biology, or Genomics.

Lab Website

 
HuBMAP Infrastructure and Engagement Component (IEC) at Pittsburgh Supercomputing Center (Computational)
The Pittsburgh Supercomputing Center is a joint computational research center with Carnegie Mellon University and the University of Pittsburgh. PSC provides university, government and industrial researchers with access to several of the most powerful systems for high-performance computing, communications and data storage available to scientists and engineers nationwide for unclassified research. PSC advances the state of the art in high-performance computing, communications and data analytics and offers a flexible environment for solving the largest and most challenging problems in research.

For the Summer of 2022 we are recruiting students for a research experience involving infrastructure that will help make HuBMAP data more accessible to the community. The research experience will provide the opportunity to:

  • Develop or extend Python packages to interface with the HuBMAP APIs to automate and facilitate processing of metadata for NIH Common Fund Data Ecosystem (CFDE) and NIH database of Genotypes and Phenotypes (dbGaP) submissions
  • Develop or implement novel algorithms to optimize pre-processing/post-processing data workflows of large datasets
  • Develop novel analysis pipelines for Apache Airflow and Jupyter notebooks
Some previous experience with programming and software engineering will be useful in most projects but is not essential. However, we would also welcome students with more extensive background and experience in programming with Python as well as experience with containerization.

 
Penn Image Computing and Science Laboratory (PICSL), University of Pennsylvania (Computational)
Led by James Gee, PhD, and Alison Pouch, PhD, the PICSL focuses on computational methods of studying anatomy in nature, and making cutting-edge image analysis methods and tools publicly available. This lab, in its work for HuBMAP and in partnership with the other Penn labs, is generating a single cell molecular map of the human female reproductive system. We are obtaining whole human reproductive systems (ovaries, Fallopian tubes, uterus) from donors and systematically dissecting them to create spatial samples for single cell molecular assays. In addition, the organs are computationally modelled to geometrically characterize their anatomy. The research involves 3-D computational modeling of the organs.

Each intern will be advised by both the PI of the lab and a graduate student or a postdoc. The students will have hands-on experience in computational research. The students will also participate in structured mentoring activity as part of Penn’s greater biomedical summer internship program. This includes attending seminars, career development guidance, and access to national seminars.

Pre-requisites: Proficiency with a programming language.

Lab Website

 
Kim Lab, University of Pennsylvania (Computational and Experimental)
Led by Junhyong Kim, this lab works at the interface of genomic technologies, computational biology, and evolutionary biology. This lab, in its work for HuBMAP and in partnership with the other Penn labs, is generating a single cell molecular map of the human female reproductive system. We are obtaining whole human reproductive systems (ovaries, Fallopian tubes, uterus) from donors and systematically dissecting them to create spatial samples for single cell molecular assays. In addition, the organs are computationally modelled to geometrically characterize their anatomy. The research involves single cell genomic assays and technology development in partnership with the O'Neill and Gregory labs, and data analysis and informatics.

The interns will be advised by both the PI of the lab and a graduate student or a postdoc. The students will have hands-on experience in laboratory and computational research. The students will also participate in structured mentoring activity as part of Penn’s greater biomedical summer internship program. This includes attending seminars, career development guidance, and access to national seminars.

Pre-requisites: For computational research, proficiency with a programming language. For experimental research, molecular biology laboratory experience.

Lab Website

 
Gregory Lab, University of Pennsylvania (Computational and Experimental)
Led by Brian Gregory, this lab works on basic RNA biology using genomic approaches and we are mainly interested in how RNA is regulated in cells. Our research: This lab, in its work for HuBMAP and in partnership with the other Penn labs, is generating a single cell molecular map of the human female reproductive system. We are obtaining whole human reproductive systems (ovaries, Fallopian tubes, uterus) from donors and systematically dissecting them to create spatial samples for single cell molecular assays. In addition, the organs are computationally modelled to geometrically characterize their anatomy. The research involves single cell genomic assays and technology development.

Experiences: Each intern will be advised by both the PI of the lab and a graduate student or a postdoc. The students will have hands-on experience in laboratory and computational research. The students will also participate in structured mentoring activity as part of Penn’s greater biomedical summer internship program. This includes attending seminars, career development guidance, and access to national seminars.

Pre-requisites: For computational research, proficiency with a programming language. For experimental research, molecular biology laboratory experience.

Lab Website

 
O’Neill Lab, University of Pennsylvania (Experimental)
Led by Kate O’Neill, this lab focuses on endometrial regeneration and factors impacting the stem cell niche in the endometrium. Our research: This lab, in its work for HuBMAP and in partnership with the other Penn labs, is generating a single cell molecular map of the human female reproductive system. We are obtaining whole human reproductive systems (ovaries, Fallopian tubes, uterus) from donors and systematically dissecting them to create spatial samples for single cell molecular assays. In addition, the organs are computationally modelled to geometrically characterize their anatomy. The research involves clinical tissue sampling, bio-banking, and pathology and single cell genomic assays and technology development.

Each intern will be advised by both the PI of the lab and a graduate student or a postdoc. The students will have hands-on experience in laboratory and clinical research. The students will also participate in structured mentoring activity as part of Penn’s greater biomedical summer internship program. This includes attending seminars, career development guidance, and access to national seminars.

Pre-requisites: Molecular biology or clinical laboratory experience.

Lab Website

 
Hagood Lab, University of North Carolina, Chapel Hill (Experimental)
Our lab studies mesenchymal cell phenotype in the context of lung development, homeostasis and remodeling (building, maintaining and repairing the lung). Our “LAPMAP” (Lung airway and parenchymal molecular atlas program) Tissue Mapping Center has generated gene expression (RNA-seq) and chromatin accessibility (ATAC-seq) data on hundreds of thousands of single cells from adult human lungs. These studies have identified known and novel subsets of mesenchymal cells that require validation and spatial localization within lung tissues using immunofluorescence (IF) and RNAscope imaging.

Internship program students can learn IF and RNAscope labeling of fixed human lung tissues and microscopic imaging. Students would also get to learn about and observe other ongoing projects in the lab, and will be encouraged to participate in HuBMAP and related consortium seminars occurring during their internship.

Prerequisites include coursework in biology and basic laboratory experience.

 
Children’s Hospital of Philadelphia and University of Pennsylvania Lab (Experimental)
Our lab at the Children’s Hospital of Philadelphia and University of Pennsylvania is mainly interested in understanding cardiovascular biology and disease. At the HuBMAP CHOP-TMC, we aim to build a single-cell multidimensional atlas of the human heart. This lab applies single-cell multiomics (snRNA-ATAC-seq) to understand the single-cell transcriptome and epigenome of the normal human heart.

Students can expect to work with a team of energetic scientists and learn about lab bench research and rigorous thinking. Students will participate in our CHOP-TMC’s effort to build a single-cell multidimensional atlas of the human heart. Specifically, they will participate in human heart specimen processing, single-cell multiomics experiments, and data analysis.

We’re looking for students who are passionate and motivated in science. This experience will be experimental, with a mix of wet bench and dry lab analysis.

 
Liu Lab, Northwestern University (Experimental)
The Liu lab at Northwestern University Feinberg School of Medicine (Chicago Downtown campus) is interested in investigating the molecular and cellular mechanisms of normal and malignant mammary epithelial stem cells in development and metastasis in respective immune microenvironment in close collaboration with Dr. Tujin Shi and Chia-Feng Tsai at Pacific Northwest National Laboratory (PNNL). As part of HuBMAP initiative, we are specifically devoted to developing and harnessing the next-generation technologies in high-resolution proteomic and phosphoproteomic analyses via mass spectrometry for the 3-D mapping of normal and abnormal human tissues. We will map normal and abnormal tissues of breast, uterine, and spleen as well as cancer stem cells and circulating tumor cells (CTCs) interacting with the tumor stroma, immune cells, and the premetastatic niche.

As part of an internship with the Liu lab, students are expected to have both experimental and computational training and experiences, including but not limited to reading literature, joining brain-storming meetings, gaining significant hands-on bench work experimental experiences (experimental design, human specimen collection, tissue culture, blood processing, fluorescence assisted cell sorting, laser capture microdissection, etc), computational analysis, deep learning, trouble-shooting, interpretation of results, and presentation of scientific data and/or journal club (oral presentation and written report). Most importantly, students are encouraged to pursue scientific passion and develop biological questions relating to tissue development, heterogeneity, and diverse interactions (different tissue regions, normal vs. malignant tissue) that can be addressed utilizing our single cell proteomics pipeline.

Previous research experience such as tissue culture, basic pipetting, and tissue handling experience (fresh and fixed tissue) would be preferred but is not a prerequisite. Recent publications for your information include (1) Communu Biol. 2021 (PMID: 33649493); (2) Cancer Discovery 2019 (PMID: 30361447); and (3) Nature Commun. 2021 (doi: 10.1038/s41467-021-25189-z).

Lab Website

 
Pacific Northwest National Laboratory (PNNL) (Experimental)
Our lab at the Pacific Northwest National Laboratory is developing methods for characterization of proteins in localized tissue regions and in single cells to assist in building 3D maps of human tissues and identifying molecular processes underpinning cellular function. Our approach incorporates innovations in microfluidic sample preparation, proteomics, mass spectrometry imaging, and multimodal data integration and visualization.

Students can expect to gain experience in tissue processing, protein measurements using state of the art mass spectrometry, data analysis and visualization. This would be a fantastic opportunity for students interested in expanding their background while working in an interdisciplinary team-based environment.

We are looking for enthusiastic students who are passionate about science and thrive in a learning culture to join our team! General lab experience or familiarity with Python or R basics would be beneficial. The internship will include a mix of wet bench and dry lab analysis.

 
Spraggins Lab, Vanderbilt University (Experimental)
The Spraggins laboratory in the Mass Spectrometry Research Center at Vanderbilt University is looking for students interested in learning about and working with next-generation molecular imaging technologies, biocomputational tools, and applications that bring together imaging mass spectrometry, highly multiplexed immunofluorescence microscopy, and spatial omics. We have several projects ongoing focused on creating comprehensive molecular atlases of the kidney, pancreas, and eye as part of the HuBMAP program.

We are seeking candidates that are interested in learning about the various analytical platforms implemented in our group and wanting an immersive research experience to better grasp the day-to-day workings of a research program. The Spraggins lab endeavors to create a dynamic workplace environment by embracing a diverse array of researchers from broad scientific, cultural, and educational backgrounds.

Candidates with a background in cell biology, biochemistry, or chemistry would be qualified. Those proficient in computational programs such as Python or R, as well as those with experience in multimodal analytical modalities such as microscopy, transcriptomics, or mass spectrometry would be well positioned to excel. This position is considered experimental, although aspects of computational modeling and analysis will be applied.

Lab website

 

Learn about our 2021 interns and the research they accomplished

In 2021, we offered a fully virtual internship for our pilot program, and our 8 interns had a rewarding, engaging experience across 6 HuBMAP labs. The 2021 interns had the opportunity to present their research findings at the August Sci/Tech webinar, a monthly gathering of Consortium members where researchers share updates on their work. You can view a full recording of the event or focus on individual accomplishments (see below) on YouTube.
Our 2021 interns said:
“It was an amazing experience and it was nice to be surrounded by professionals that truly cared about us and wanted to make sure that we succeeded.”

“The most exciting thing about the HuBMAP internship is that you can combine science and technology to create something that will contribute to the biotech community.”

“[I was excited by] the fact that I was able to work so closely with professionals in a field that I one day would like to be in. I was so amazed by how well versed and well informed everyone was. It was truly inspirational.”

“I loved hearing about everyone’s research and being able to present everything I’ve learned in front of a group with similar interests.”

“[I enjoyed] being able to learn hands-on with new programs and integrating those with research.”

“My mentors and PI were so helpful and knowledgeable. They helped me so much during this process and in every meeting that I had with them I felt that I got to know them and the work they do.”

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