Bioinformatics and Computational Biology Professional

Description

Are you passionate about identifying, defining, and solving some of the hardest problems faced by the nation?

Do you love transitioning research into real-world solutions?

Do you enjoy working with interdisciplinary teams?

If so, we are looking for someone like you to join our team at APL!

The Applied Biological Sciences Group (QLA), located within the Asymmetric Operations Sector (AOS), is committed to APL's mission to provide critical contributions to critical challenges. We seek a highly motivated scientist or engineer with expertise in molecular biology, bioinformatics, and computational biology to develop technical solutions to address the biological threats facing our nation. Candidates should be curious, collaborative, and dedicated to leveraging world class expertise to develop real-world solutions for national security and health application spaces as part of a dynamic and innovative interdisciplinary team.

APL works across the US Government applying the full spectrum of science and engineering to improve the nation's ability to safely mitigate biological threats. We partner closely across the whole of the Johns Hopkins enterprise, and with collaborators in government, academia, and industry, to develop innovative science and technology solutions to biosecurity challenges. We strive to ensure the health of individuals and the nation through applied research, which drives development and implementation of ground-breaking capabilities in sensing and detection, threat characterization, modeling and simulation, and more.

As a bioinformatics and computational biology professional, you will...

• Lead and support bioinformatics and data science aspects of genomics and systems biology projects.
• Perform and lead analysis using open-source tools and custom pipelines on a High-Performance Computing (HPC) Cluster.
• Perform and lead bioinformatics tasks operating in a Linux environment, using at a minimum BASH, Python, and R languages.
• Lead and support sequence analysis on Illumina, PacBio, and Oxford Nanopore data.
• Identify and implement analysis tools for multi- 'omics data mining and fusion.
• Lead and support novel bioinformatics and computational biology analyses approaches and tool development.
• Leverage your technical expertise and passion for applied research to lead the development of new proposals for intramural and extramural research aimed at pursuing high-risk, high-reward ideas.

Qualifications

You meet our minimum qualifications for the job if you have...

• A Master's degree in Bioinformatics, Computer Science, Molecular Biology, Applied Mathematics or another field relevant to the duties as described above.
• At least one year of professional work experience.
• Experience developing and leading bioinformatics and computational biology efforts.
• Exceptional interpersonal skills and the ability to clearly communicate complex topics.
• Competent understanding of statistics and ability to compare and contrast traditional and biostatistics methods to separate noise or quantify significance within multiple 'omics data sets
• Ability to work across Windows/iOS and Linux systems, and efficiently manage large data sets for a variety of projects
• Familiarity with industry-accepted tools and approaches for biological data analysis including but not limited to metagenomics classification, RNA-Seq, differential expression, etc.
• Understanding of assembly and alignment techniques of next-generation sequence fragments and computational resources required to achieve high throughput results.
• Ability to model and simulate biological systems in silico using mathematical concepts such as matrices, differential equations, and standard modeling concepts
• Familiarity with algorithms in computer science and applied mathematics commonly used for analyzing complex biological data, such as Expectation-Maximization, Dynamic Programming, K-Nearest-Neighbors (KNN), Support Vector Machines (SVMs), Universal Differential Equations (UDEs), and other AI/ML approaches to data analysis and decision support.
• Ability to troubleshoot algorithms and implement software programs for the analysis of such data.
• Experience with cluster computing environment and/or resource schedulers for high throughput (parallel) computations, and heuristics for dealing with large data sets; Ability to scale analyses across computational loads
• Demonstrated ability to keep up to date with open-source software and published literature of new tools and examine capabilities and limitations of such tools for sponsor related requirements.
• Eligibility to obtain Secret level clearance. If selected, you will be subject to a government security clearance investigation and must meet the requirements for access to classified information. Eligibility requirements include U.S. citizenship.

You'll go above and beyond our minimum requirements if you have...

• Experience performing (or familiarity with) laboratory sequencing preparations and workflows
• Experience with wet lab molecular biology techniques
• Experience developing and leading multidisciplinary teams and projects
• Experience with BASH, Python, R and Linux environments. Familiarity with Julia, Claude, and Rust
• Ability to utilize and implement Agentic AI tools
• Experience working in Unclassified and Classified areas
• A publication record in computational biology and/or bioinformatics analysis
• A PhD in Bioinformatics, Computer Science, Molecular Biology, Applied Mathematics

About Us

Why Work at APL?

The Johns Hopkins University Applied Physics Laboratory (APL) brings world-class expertise to our nation's most critical defense, security, space and science challenges. While we are dedicated to solving complex challenges and pioneering new technologies, what makes us truly outstanding is our culture. We offer a vibrant, welcoming atmosphere where you can bring your authentic self to work, continue to grow, and build strong connections with inspiring teammates.

At APL, we celebrate our differences of perspectives and encourage creativity and bold, new ideas. Our employees enjoy generous benefits, including a robust education assistance program, unparalleled retirement contributions, and a healthy work/life balance. APL's campus is located in the Baltimore-Washington metro area. Learn more about our career opportunities at https://www.jhuapl.edu/careers.

All qualified applicants will receive consideration for employment without regard to race, creed, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, genetic information, veteran status, occupation, marital or familial status, political opinion, personal appearance, or any other characteristic protected by applicable law. APL is committed to providing reasonable accommodation to individuals of all abilities, including those with disabilities. If you require a reasonable accommodation to participate in any part of the hiring process, please contact Accessibility@jhuapl.edu.

The referenced pay range is based on JHU APL's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level with consideration for internal parity. For salaried employees scheduled to work less than 40 hours per week, annual salary will be prorated based on the number of hours worked. APL may offer bonuses or other forms of compensation per internal policy and/or contractual designation. Additional compensation may be provided in the form of a sign-on bonus, relocation benefits, locality allowance or discretionary payments for exceptional performance. APL provides eligible staff with a comprehensive benefits package including retirement plans, paid time off, medical, dental, vision, life insurance, short-term disability, long-term disability, flexible spending accounts, education assistance, and training and development. Applications are accepted on a rolling basis.

Minimum Rate

$100,000 Annually

Maximum Rate

$245,000 Annually