Senior Scientist, Bioinformatics

A career at Resilience is more than just a job - it's an opportunity to change the future.

Resilience is a technology-focused biomanufacturing company that's changing the way medicine is made. We're building a sustainable network of high-tech, end-to-end manufacturing solutions to better withstand disruptive events, serve scientific discovery, and reach those in need.

For more information, please visit www.resilience.com

RESILIENCE (National Resilience, Inc.) is a first-of-its-kind manufacturing and technology company dedicated to broadening access to complex medicines and protecting biopharmaceutical supply chains against disruption. Founded in 2020, the company is building a sustainable network of high-tech, end-to-end manufacturing solutions to ensure the medicines of today and tomorrow can be made quickly, safely, and at scale. RESILIENCE will offer the highest quality and regulatory capabilities, and flexible and adaptive facilities to serve partners of all sizes. By continuously advancing the science of biopharmaceutical manufacturing and development, RESILIENCE frees partners to focus on the discoveries that improve patients' lives.

Position Summary & Responsibilities

• The Senior Bioinformatics Scientist will provide leadership and expertise in bioinformatics methods to our product development teams with bioinformatics pipelines and analysis towards better and more affordable cell therapy, personalized medicine solutions.
• Resilience is looking for a smart, motivated scientist who enjoys taking on complex challenges, works well in an agile, dynamic environment, and cares about high-quality products and best practices.
• The ideal candidate thrives on the applications of NGS data analysis (in particular using AI and ML) and is passionate about learning.
• Resilience rewards initiative, curiosity, a bias for action, a problem-solving attitude, and a desire to bring innovative, simplified solutions to complex problems that ultimately impact patient care.
• Provide continuous standardization, improvements, and features on our single-cell data analysis pipelines, including both internal and external software tools.
• Develop new data analysis plans and methods and execute on them to provide improved single-cell data analysis and visualization solutions.
• Review, implement, troubleshoot, and improve analytic analysis methods developed by others internally or externally, integrate standard and emerging AI/ML models as appropriate.
• Build and deploy bioinformatics pipelines that leverage NGS applications including RNAseq, single-cell DNA/RNA, CITE-seq, WGS, and targeted sequencing, among other data types.
• Develop robust, modular, and reliable data monitoring and visualization tools in collaboration with our Research and Software team to understand and interpret data.
• Work closely with cross-functional teams, providing computational tools and resources for analysis of large biological data sets.

Minimum Qualifications

• Required demonstrable experience with next-generation sequencing single-cell data analysis from transcriptomics, proteomics, genomics, and epigenomics.
• Strong technical expertise analyzing cellular genomics data including single cell sequencing and multi-modal 'omics data types is required.
• Hands-on work experience with large complex data sets, programming languages such as Python and R, and translation of results to a non-technical audience.
• Experience in high-performance computing and/or cloud computing.
• Outstanding collaboration skills that enable effective partnerships with professionals from different technical backgrounds.
• Good knowledge of software design principles including git, docker, and markdown documentation.
• General understanding of molecular biology and wet-lab 'omics technologies is preferred.

Preferred Qualifications

• MSc with 5+ years relevant experience or Ph.D. with 2+ years relevant experience, or equivalent, in a quantitative field, e.g., Bioinformatics, Computation Biology, etc.
• Experience with optimization and statistical data analysis tools is a plus.
• Strong core in genomics, molecular biology, NGS, with proven track record in translating complex biological questions into computational tools that solve problems.
• Experience with integration analysis of NGS data sources in the context of immune cell therapy is a plus.
• Relevant experience applying NGS to Immunology or Immuno-oncology is a plus.

Equal Opportunity Statement

At Resilience we believe that the business of business is to improve the state of our world. We are committed to creating a workforce that reflects society, to maintaining inclusive programs and to providing equal opportunities to qualified individuals.

Resilience is an equal employment opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, physical or mental disability, genetic information or characteristic, or other non-job-related characteristics protected by applicable law.Applicants who require reasonable accommodations for any portion of the job application process may contact careers@resilience.com for assistance. Resilience welcomes all.

Resilience does not accept unsolicited headhunter and agency resumes. Resilience will not pay any third-party agency or company that does not have a signed agreement with Resilience.

Resilience is an Equal Employment Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, disability status, physical or mental disability, genetic information, or characteristic, or other non-job-related characteristics or other prohibited grounds specified in applicable federal, state, and local laws. Requests for reasonable accommodation can be made at any stage of the recruitment process.