Computational Scientist - Single-Cell Sequencing / Machine Learning...

Full and partial remote work options are available with hiring manager approval. Periodic travel to Farmington and/or Bar Harbor campuses expected in the future.

Summary

The Jackson Laboratory (JAX) is seeking a computational biologist to join a subteam of the Computational Sciences group active at the intersection of single-cell biology and machine learning. The successful candidate will apply and develop bioinformatics, statistical, machine learning, and deep learning approaches to analyze single-cell sequencing and spatial expression data generated at JAX's Single-Cell Biology Laboratory (SCBL), including single-cell RNA-seq (sc RNA-seq), single-nucleus ATAC-seq (sn ATAC-seq), and multiomic single-nucleus RNA-/ATAC-seq data. The primary responsibilities of the Computational Scientist include deriving biological insight from single-cell sequencing data across a range of diseases, including cancer, dementia, and type 2 diabetes and developing novel methods for computational... analysis of emerging technologies, such as multiomic sequencing and spatial transcriptomics. Team members are also involved in single-cell imaging analysis (e.g., of imaging mass cytometry) and the position offers opportunities to integrate sequencing and imaging data.

The Computational Scientist will stay current in the latest single-cell sequencing analysis methods and their biological application by attending and presenting at conferences. They will expand their professional network through collaborations with faculty across JAX campuses and with external investigators and consortia. Finally, they will have significant growth opportunities to develop novel and evaluate existing methods in the rapidly evolving field of single-cell and multiomic sequencing and to deploy them in advancing biological discoveries.

A Successful Computational Scientist will have:

• Experience analyzing sc RNA-seq and/or sn ATAC-seq data (e.g., using Seurat or Scanpy), including integrating datasets and data modalities.
• Expertise applying and developing statistical and machine learning approaches to address questions in biology, such as: regression, Bayesian modeling, random forests, ensemble methods, clustering, survival analysis, and dimensionality reduction.

Characteristic distinction from Assistant to Associate Computational Scientist includes increased ability to work independently, liaise directly with biologists, develop in-depth knowledge in selected biological disciplines, provide biological interpretation of results, contribute to or lead grant submissions, and mentor more junior Computational Scientists.

Responsibilities

• Analyze sc RNA-seq, sn ATAC-seq, multiomic RNA-/ATAC-seq, and/or spatial transcriptomics data from quality control through generation of results, in collaboration with faculty on the Farmington, CT and Bar Harbor, ME campuses and under minimal supervision.
• Develop and publish novel methods for predicting disease and biological phenotypes from single-cell sequencing data, making them accessible to the community as well-documented packages/libraries shared in online repositories (e.g., github, Bioconductor).
• Attend and present at scientific meetings to maintain and advance technological and scientific expertise at JAX.
• Provide leading contributions to internal and external grant applications.
• Participate in departmental and project activities, participate in conducting courses and workshops at JAX, help students and scientists, participate in CS meetings and present results to JAX community and at conferences and workshops as assigned.

Qualifications

• PhD in Computational Biology, Bioinformatics, Computer Science, Biostatistics, Physics, or relevant area (assistant and associate).
• Assistant Level: 0-2 years of experience excluding time spent to obtain PhD.
• Associate Level: 2-4 years of experience excluding time spent to obtain PhD.
• Excellent verbal and written communication skills.
• Demonstrated ability to develop and execute a scientific narrative, as indicated by lead author, peer-reviewed publications in impactful journals.
• Proficiency in Python and/or R in a Linux environment.
• Strong initiative, and motivation to learn new technologies and biological domains.
• An ability to explore and research new challenges creatively and with limited supervision.

The ideal candidate will have one or more of the following:

• A solid understanding of biology (molecular, immunology, cancer or other disease) and prior experience collaborating with biologists and clinicians.
• Familiarity with deep learning libraries (e.g., tensorflow).
• Experience with software development environments (e.g., git/github, conda, Docker).

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