Summary

The Carter Lab has an opening for a Computational Scientist in Alzheimer’s disease research. This position will be part of our ongoing studies that seek to understand the origins, progression, and potential treatments of Alzheimer’s disease through multiple experimental platforms.

We are seeking to answer two main computational questions:

• How can we combine multi-omics, biomarker, and bioimaging data across multiple species to model the origins, progression, and therapeutic interventions for Alzheimer’s disease?
• How can we implement rigorous preclinical testing of precision therapeutics that target Alzheimer’s disease pathways in advanced mouse models?

Our unique position in the MODEL-AD, TREAT-AD, and Marmo-AD consortia provides a network of collaborations spanning over a dozen institutions. We have abundant access to mouse, cellular, and primate model systems that we pair with human studies to maximize translational utility and accelerate precision approaches to Alzheimer’s treatments. The multi-disciplinary environment enables iterative cycles of experimentation and data analysis.

Data scientists interested in creative machine learning approaches to data integration are especially encouraged to apply. We are dedicated to open science and establishing an inclusive culture to expand our vision of scientific progress.

Key Responsibilities
The successful candidate will perform independent computational analyses of multiple data sets to infer multi-scale hypotheses of Alzheimer’s disease development. They will document and report results to center colleagues for collaborative experimental validation. They will lead efforts to disseminate research results including all data and analysis via publications, data sharing, and presentations to consortium peers and at scientific meetings. They will extend our existing work in new directions and potentially seek external funding for independent projects.

Knowledge, Skills, and Abilities

• Ph.D. in bioinformatics, computational biology, biostatistics, or related field is required
• Assistant level will possess 0-2 years of experience in Bioinformatics research, excluding time spent to obtain Ph.D.
• Associate Level will possess 2-5 years of experience in Bioinformatics research, excluding time spent to obtain Ph.D.
• Exceptional verbal and written communication skills
• Demonstrates ability to be collaborative across disciplines
• Demonstrated experience managing projects and collaborations are key
• Prior successes in and desire to contribute to team projects on an ongoing basis is a must.
• Demonstrated writing ability as evidenced by significant contribution/leadership role in bringing a minimum of one 1st author paper from graduate work to publication is highly preferred

About JAX:

The Jackson Laboratory (JAX) is an independent, nonprofit biomedical research institution with more than 2,400 employees. Headquartered in Bar Harbor, Maine, it has a National Cancer Institute-designated Cancer Center in Augusta, Maine, a genomic medicine institute in Farmington, Connecticut, and facilities in Ellsworth, Maine, Sacramento, California, and Shanghai, China. Its mission is to discover precise genomic solutions for disease and empower the global biomedical community in the shared quest to improve human health.

JAX employees work in a collaborative, value-driven, and team-based environment where the focus is on advancing science and improving patients’ lives. Researchers apply genetics to increase the understanding of human disease and advance treatments and cures for cancer, neurological and immune disorders, diabetes, aging, and heart disease. JAX was voted among the top 15 “Best Places to Work in Academia” in the United States in a poll conducted by The Scientist magazine!

EEO Statement:

The Jackson Laboratory provides equal employment opportunities to all employees and applicants for employment in all job classifications without regard to race, color, religion, age, mental disability, physical disability, medical condition, gender, sexual orientation, genetic information, ancestry, marital status, national origin, veteran status, and other classifications protected by applicable state and local non-discrimination laws.