Computational Biologist - Machine Learning, Antigen Map

Employer
Adaptive Biotechnologies
Location
Seattle, Washington, US
Salary
Competitive
Posted
Jul 28, 2021
Closes
Jul 30, 2021
Ref
2266033079
Discipline
Adaptive Management
Employment Type
Full time
Salary Type
Salary
We are powering the age of immune medicine- you can too. At Adaptive, our goal is to meaningfully improve people's lives by learning from the wisdom of the adaptive immune system.
As an Adapter, you will be surrounded by driven colleagues who think boldly to pursue ground-breaking innovation. You will experience meaningful challenge in your work and be fueled by motivating energy knowing you make a difference in people's lives.
You belong here- come discover your story at Adaptive.
Position Overview
The Antigen Map project is a collaboration between Adaptive and Microsoft Healthcare to map and decode the human immune system, nature's most finely tuned diagnostic. Together, we are using immunosequencing, proprietary computational modeling and machine learning to map T-cell receptor (TCR) sequences to the antigens they bind. Using this data, we aim to translate the natural diagnostic capability of the immune system into the clinic.
The Antigen Map is seeking a thoughtful computational biologist who is enthusiastic about data analysis, machine learning, the immune system, and improving human health. You will join a team within the Antigen Map that is mining large clinical datasets for disease-associated TCRs and using them to build machine learning-based diagnostics in cancer, autoimmune, and infectious disease.
We are looking for someone with substantial experience in solving classification problems in biological datasets and communicating results to diverse audiences. Outstanding candidates will have demonstrated the ability to work independently and as part of an interdisciplinary team. Adaptive strongly values professional development, and we are committed to helping team members grow in their careers.
Responsibilities
Perform quick and thorough analyses of DNA sequencing of T-cell receptors and other clinical data to understand confounders, make descriptive figures, and address key scientific questions.
Develop and apply robust machine learning methods that combine biological insights with rapidly evolving data.
Communicate with external collaborators to design experiments and manage clinical metadata
Present results to a wide variety of stakeholders, from wet lab and computational scientists to clinical, commercial, and executive team members
BE A PROBLEM SOLVER: communicate well, ask questions, proactively eliminate bottlenecks, and be the person people go to when they want a job done right.
Requirements
Graduate degree PhD in Computer Science, Statistics, Biostatistics, Genomics, or related field and 2+ years of relevant experience (or a Master's degree with 10+ years of experience)
Proficiency in Python
Demonstrated ability to work on multidisciplinary teams
Experience in presenting technical material to diverse audiences
Experience with detailed analysis of next-generation sequencing datasets
(Preferred) Experience with clinical data and samples (e.g., clinical trials, observational studies)
(Preferred) Extensive experience and domain knowledge in infectious or autoimmune disease
Adaptive Biotechnologies is proud to be an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. Equal Opportunity Employer/Veterans/Disabled
NOTE TO EMPLOYMENT AGENCIES: Adaptive Biotechnologies values our relationships with our Recruitment Partners and will only accept resumes from those partners whom have been contracted by a member of our Human Resources team to collaborate with us. Adaptive Biotechnologies is not responsible for any fees related to resumes that are unsolicited or are received by any employee of Adaptive Biotechnologies who is not a member of the Human Resources team.
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