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Mason Alert:

George Mason University in-person classes are cancelled and administrative offices are closed Monday Jan 26, due to inclement weather. For more information about campus operations go here: https://www.gmu.edu/campus-status.

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George Mason University
Job Opportunity

Intern, Machine Learning for Molecule Design (MS/PhD) at Calico Life Sciences

Full Job Details

Employer: Calico Life Sciences

Expires: 02/15/2026

Who We Are:Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science, and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.Position description:Calico is seeking an intern to join the Machine Learning (Molecule Design) group. To succeed, you will need to be an enthusiastic team player, detail-oriented, extremely organized and comfortable working on complex problems.  In this position you will perform research to advance the state-of-the-art in modelling binding affinity. The successful candidate will work closely with members of the Machine Learning (Molecule Design) group on developing ranking models for molecular design applications and integrating them into a molecule design framework to generate designs.Responsibilities: Gain expertise in state-of-the-art research in machine learning based molecule designImplement novel ideas for ranking the designsDevelop benchmarks to validate models and compare performance to existing internal and public methodsCommunicate results through presentation and/or publicationPosition requirements:Currently pursuing a MS or PhD degree, in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics,  Statistics, Applied Mathematics, Physics or related field Experience applying machine learning to solve challenging problems, and with modern machine learning techniques Knowledge of Python and deep learning frameworks (such as PyTorch, TensorFlow, JAX)Strong analytical and quantitative problem solving skillsDetail-oriented and organizedStrong teamwork and communication skillsSelf-motivated with a “can-do” attitudeFlexible, able to respond quickly to shifting priorities and able to multitaskNice to have:Experience in molecule design, cheminformatics, ranking or geometric deep learningAbout our Program:Calico’s internship program is a paid 12-week program over the summer for students interested in understanding the fundamental science of aging and finding treatments for the associated and intractable diseases. Working in a collaborative environment and fully embedded in one of our labs/teams, Calico interns tackle a unique project under the mentorship of at least one of our scientists or engineers. Program Features:3-month summer timelineIn-person experience at our offices in South San FranciscoMatching with at least one Calico mentorGroup supplemental activities weekly featuring guest speakers, Senior Leadership spotlights, and discussion groups on aging science, our drug development approach, and moreEnd-of-summer company-wide project showcase and poster sessionCompetitive compensation ($45 - $70/hour) and monthly living expenses stipend Program Eligibility:Able to work in-person at our offices in South San FranciscoFree for a consecutive period of 11-12 weeks in June, July, and AugustNot graduating before December 2026Exception for students enrolling into a graduate degree program in Fall 2026Must be enrolled in a US universityMust apply by application deadline: February 1, 2026.

* The programs and services offered by George Mason University are open to all who seek them. George Mason does not discriminate on the basis of race, color, religion, ethnic national origin (including shared ancestry and/or ethnic characteristics), sex, disability, military status (including veteran status), sexual orientation, gender identity, gender expression, age, marital status, pregnancy status, genetic information, or any other characteristic protected by law. After an initial review of its policies and practices, the university affirms its commitment to meet all federal mandates as articulated in federal law, as well as recent executive orders and federal agency directives.