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Company Description

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on Twitter, Facebook, Instagram, YouTube and LinkedIn.

Job Description

Single-Cell Machine Learning Intern Overview

Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for AbbVie Interns.

AbbVie's Genomics Research Center (GRC) is widely recognized as a center of excellence in various fields, including bioinformatics, functional genomics, human genetics, pharmacogenomics, and the study of multiple population cohorts, with a database containing over 1 million genomes. The GRC's work extends beyond research and development, encompassing areas such as process sciences and corporate strategy. It plays a vital role in our pursuit of world-class genetics and genomics research by focusing on identifying the most suitable targets and enhancing our understanding of not only human disease biology but also the behavior and response of our drugs in clinical trials.

The intern will be co-mentored by scientists in the Bioinformatics Genomic Sciences group, within the GRC to develop robust methods for reference-based, automated cell type assignment in single-cell RNA datasets. This role will provide the candidate with exposure to multiple, diverse therapeutic areas (TAs) and bioinformatics disciplines. A successful internship will require focused delivery on at least one tissue, but an exceptional candidate will have the opportunity to abstract their technique across multiple TAs.

This internship will be based in North Chicago, IL.

Key responsibilities include:

• Draw upon multiple high-quality single-cell/single-nucleus “atlas” data resources

• Evaluate different methods for reference-based cell-type assignment

• Lay the foundations for a best-in-class statistical model

• Work across TAs to identify crucial differentiators in Atlas resources

• Identify gaps in methodology and resources

Qualifications

Minimum Qualifications

• Currently enrolled in university, pursuing a PhD in Bioinformatics, Statistics, Applied Mathematics, Machine Learning or other related field

• Must be enrolled in university for at least one semester following the internship

• Familiarity with single-cell RNA-Seq methods

• Expertise in R, Python, or other high-dimensional statistical-modelling enabled language

Preferred Qualifications

• Expected graduation date between December 2025 – July 2026

• Exposure to Pytorch/Keras/Tensorflow ecosystem

• Experience writing and maintaining packaged software

• Exposure to “out of memory”/on-disk matrix computation paradigms

• Previous experience with million+ cell datasets

• Exposure to transfer-learning methodology

• Scientific demeanor and curiosity

Benefits and Amenities

• Competitive pay

• Relocation support for eligible students

• Select wellness benefits and paid holiday / sick time

• Co-mentorship from established scientific and industry leaders

Equal Employment Opportunity

At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.

Additional Information

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.​

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law. ​

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AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html