ASPIRE Intern – Studio D3: AI Models of Human Immune Response

Qualifications

• Bachelor’s degree
• Demonstrated commitment to science
• This is a fully computational project requiring strong computational coding experience (computational science, machine learning, physics, applied math, or similar)
• The successful candidate will have strong skills in a form of quantitative scientific analysis such as machine learning, data analysis, statistics, or similar
• Must have completed a Bachelor’s degree prior to the start of the program, and no earlier than December 1, 2023, and must not have an advanced degree in field relevant to the role/project
• Must be able to start in June or July 2026 and commit to the full one-year program, which will end on May 28, 2027
• Must be authorized to work in the U.S. for the program duration
• Must be 18 years of age or older

Benefits

• Position Type/Expected Hours of Work
• Annualized Salary
• $61,048 (non-negotiable)
• ASPIRE Interns (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute’s Benefits Guide
• These benefits include medical, dental, vision, and basic life insurance
• Employees are also eligible to enroll in the Allen Institute’s 401k plan
• Paid time off is also available as outlined in the Allen Institutes Benefits Guide

Responsibilities

• The Studio D3 interns will be part of a cohort aimed at tackling problems of interest across biological areas, using methods from any of a variety of computational approaches from dynamical systems to machine learning and beyond
• The successful applicant will bring a strong computational background along with an interest in applying those skills to pressing biological questions
• Specifically, the Intern will work with large-scale, in-house human immune cell transcriptomic datasets to evaluate and potentially develop new single-cell foundation models that generate robust sample- and donor-level embeddings to capture human immune variations
• These embeddings will be a core component to build predictive models designed to forecast functional immune outcomes, such as individual responsiveness to vaccination and the progression of autoimmune diseases
• Furthermore, the intern will perform in-depth analysis of the resulting single-cell and donor embeddings to identify and characterize key immune subsets, regulatory gene programs, and critical multicellular network interactions that ultimately shape these immune functions
• The successful applicant will be part of a cohort of interns dedicated to quantitative biological problems
• Gain a foundational understanding of the human immune system and its roles in health and diseases
• Learn methods for single-cell transcriptomic data analysis, including the use and interpretation of single-cell foundational models
• Develop AI models for transcriptomic data to predict immune responses to vaccination and autoimmune disease progression
• Learn to read both computational methods and immunology literature critically to inform model design and interpretation
• Learn to write clean, reproducible and documented code in a collaborative setting using GitHub version control and code reviews
• Communicate progress and findings to relevant teams within the Allen Institute
• This role is currently working onsite and is expected to work onsite for the majority of working hours
• ASPIRE Interns are expected to participate as fully-engaged team members, attending and participating in team meetings, presenting on their work, etc
• Aside from program activities, interns are expected to work full-time as regular team members unless otherwise approved by their manager

Full Description

ASPIRE Intern – Studio D3: AI Models of Human Immune Response

The mission of the Allen Institute is to understand the principles that govern life and to advance health.

Our creative and multi-dimensional teams focus on answering some of the biggest questions in bioscience.

We accelerate foundational research, catalyze bold ideas, develop tools and models, and openly share our science to make a broad, transformational impact on the world.

The Allen Institute is searching for an ASPIRE Intern for its new Studio D3.

Studio D3 develops and applies cutting-edge theoretical models, analytical frameworks, and scalable computational methods to extract principles that govern biology from multimodal biological data.

The Allen Institute has collected and openly shared some of the largest datasets in life sciences.

By integrating computation, data science, and quantitative modeling into the research ecosystem, Studio D3 helps drive discovery across diverse biological disciplines.

The Studio D3 interns will be part of a cohort aimed at tackling problems of interest across biological areas, using methods from any of a variety of computational approaches from dynamical systems to machine learning and beyond.

The successful applicant will bring a strong computational background along with an interest in applying those skills to pressing biological questions.

The Intern will develop and apply advanced AI models that uncover novel mechanistic insights into the human immune system in health and disease.

Specifically, the Intern will work with large-scale, in-house human immune cell transcriptomic datasets to evaluate and potentially develop new single-cell foundation models that generate robust sample- and donor-level embeddings to capture human immune variations.

These embeddings will be a core component to build predictive models designed to forecast functional immune outcomes, such as individual responsiveness to vaccination and the progression of autoimmune diseases.

Furthermore, the intern will perform in-depth analysis of the resulting single-cell and donor embeddings to identify and characterize key immune subsets, regulatory gene programs, and critical multicellular network interactions that ultimately shape these immune functions.

The successful applicant will be part of a cohort of interns dedicated to quantitative biological problems.

At the Allen Institute, we believe that science is for everyone – and should be open to everyone.

We are dedicated to combating biases and reducing barriers to STEM careers more broadly.

We also believe that science is better when it includes different perspectives and voices.

We strive to make the Allen Institute a place where everyone feels like they belong and are empowered to do their best work in a supportive environment.

We are an equal-opportunity employer and strongly encourage people from all backgrounds to apply for our open positions.

Applications must be received by January 12, 2026, to be considered.

Educational Objectives

• Gain a foundational understanding of the human immune system and its roles in health and diseases

• Learn methods for single-cell transcriptomic data analysis, including the use and interpretation of single-cell foundational models

• Develop AI models for transcriptomic data to predict immune responses to vaccination and autoimmune disease progression

• Learn to read both computational methods and immunology literature critically to inform model design and interpretation

• Learn to write clean, reproducible and documented code in a collaborative setting using GitHub version control and code reviews

• Communicate progress and findings to relevant teams within the Allen Institute

Required Education and Experience

• Bachelor’s degree

• Demonstrated commitment to science

• This is a fully computational project requiring strong computational coding experience (computational science, machine learning, physics, applied math, or similar)

• The successful candidate will have strong skills in a form of quantitative scientific analysis such as machine learning, data analysis, statistics, or similar

Work Environment

• Open office environment

Position Type/Expected Hours of Work

• This role is currently working onsite and is expected to work onsite for the majority of working hours. The primary work location for this role is 615 Westlake Ave N., with flexibility to work remotely on a limited basis.

Additional Eligibility Qualifications

• Must have completed a Bachelor’s degree prior to the start of the program, and no earlier than December 1, 2023, and must not have an advanced degree in field relevant to the role/project

• Must be able to start in June or July 2026 and commit to the full one-year program, which will end on May 28, 2027

• Must be authorized to work in the U.

S. for the program duration

• Must be 18 years of age or older

Additional Comments

• ASPIRE Interns are expected to participate as fully-engaged team members, attending and participating in team meetings, presenting on their work, etc.

• Aside from program activities, interns are expected to work full-time as regular team members unless otherwise approved by their manager

• Please note, this opportunity offers relocation assistance

• **Please note, this opportunity requires U.

S work authorization and does not sponsor work visas**

Annualized Salary

• $61,048 (non-negotiable)

Benefits

• ASPIRE Interns (and their families) are eligible to enroll in benefits per eligibility rules outlined in the Allen Institute’s Benefits Guide.

These benefits include medical, dental, vision, and basic life insurance.

Employees are also eligible to enroll in the Allen Institute’s 401k plan.

Paid time off is also available as outlined in the Allen Institutes Benefits Guide. Details on the Allen Institute’s benefits offering are located at the following link to the Benefits Guide: https://alleninstitute.org/careers/benefits.

It is the policy of the Allen Institute to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law.

In addition, the Allen Institute will provide reasonable accommodations for qualified individuals with disabilities.