Intern, Cellular Research and Innovation Computational Biology
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 Cellular Research and Innovation (CRI) group at Adaptive uses powerful experimental platforms and high-throughput sequencing to study the adaptive immune system and discover lymphocyte receptors with therapeutic potential. The CRI Computational Biology team works with cellular immunologists to design experiments, analyze and interpret data, develop process improvements, and create novel algorithms and bioinformatic pipelines.
The CRI Computational Biology team is seeking an Intern, Computational Biology who is enthusiastic about data science, genetics, and immunology to apply their skills at improving human health. A variety of projects are available, depending on the applicant's background and interests. Available projects relate to Adaptive's immune medicine therapeutic research programs, ranging from target discovery, lead identification, and meta-analysis. This position is intended for late-stage graduate students considering careers in industry.
You will join a collaborative Computational Biology group that conducts analyses to support key decisions within the company and creates innovative solutions to drive our research and product development. 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.
Key Responsibilities and Essential Functions
- Conduct exploratory data analyses to address key research questions.
- Collaborate with computational biologists to improve algorithms and analysis methods through data-driven insights.
- Write reproducible code.
- Present results to a wide variety of stakeholders within the company.
- 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.
Position Requirements (Education, Experience, Other)
Required
- Currently enrolled in a MS/PhD program in Computational Biology, Computational Immunology, Genomics, or related field
- Proficiency in at least one common coding language for data science (R, Python, etc.; Python preferred)
- Experience working on the command line, version control, and high performance compute environments
Preferred
- Experience analyzing biological datasets, including data cleaning, visualization, and statistical analysis
- Experience working with wet lab biologists and/or strong background in immunology
- Experience with high-throughput sequencing data
- Good oral and written communication skills
#LI-Remote
Where permitted by applicable law, applicant must have received, or be willing to receive, a COVID-19 vaccine by date of hire to be considered for employment.
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.