COMPUTATIONAL BIOLOGIST ASSOCIATE

Uses existing tools to build data processing pipelines to convert raw data into formats compatible with conventional statistical and bioinformatics analysis and visualization. Evaluates new technologies and methods for implementation of novel tools when necessary. Performs routine analysis for which established tools exist and are considered reliable. Keeps up with the computational biology literature and computational method development to assure pipeline components are up to date. Under the supervision of a senior computational biologist, aids in the development of pipelines following best computational biology practices (e.g: use a workflow management system) to deploy pipelines in a rigorous, scalable, and reproducible manner. Monitors, downloads, organizes, and manages data from public data repositories or generated by collaborates. Develops and deploy web-applications for the interactive visualization of high-throughput data to aid in data interpretation. Helps to formulate specific aims, provides feedback for experimental design, and develops data analysis plans and statements of work . Develops timelines and components for larger projects; masters multi-tasking so that complex projects involving many interdisciplinary individuals move forward smoothly.

We are seeking a talented and motivated Computational Biologist Associate to join our team in developing the CHARM (Collecting, Harmonizing, Analyzing, Reasoning about, and Manipulating) framework as part of the Precision Medicine lnstitute's participation in the ARPA-H Biomedical Data Fabric program. The CHARM framework is a cutting-edge, open-source end-to-end toolchain that aims to revolutionize the way biomedical data is collected, curated, and analyzed by leveraging advanced Al techniques, including generative Al and knowledge graphs. As a Computational Biologist Associate, you will work closely with our interdisciplinary team of experts in biomedical informatics, data science, computational biology, and artificial intelligence to design, implement, and optimize various components of the CHARM framework. Your contributions will help drive the development of innovative tools and techniques that can accelerate biomedical research and improve patient outcomes.

If you are passionate about advancing biomedical research through innovative software engineering and Al techniques, we encourage you to apply for this exciting opportunity to join our team and contribute to the development of the groundbreaking CHARM framework.

Responsibilities:

• Collaborate with the research team to design and implement software components for the CHARM framework
• Develop and optimize algorithms for data harmonization, integration, and analysis
• Integrate advanced Al techniques, such as generative Al and knowledge graphs, into the CHARM framework
• Participate in code reviews and ensure the maintainability, scalability, and robustness of the codebase
• Contribute to the documentation and testing of the CHARM framework
• Stay up-to-date with the latest trends and best practices in software engineering and Al
• Perform other duties as assigned

Salary Range: $77,640 - $126,170

Master's degree in a related field OR Bachelor's degree in related field and two (2) years of related experience. Work experience may NOT substitute for education requirement.

Preferred:

• Strong programming skills in languages such as Python and JavaScript
• Experience with software development best practices, including version control (e.g., Git), testing, and documentation
• Familiarity with Al techniques, such as machine learning and deep learning
• Knowledge of biomedical data formats, ontologies, and standards (e.g., FHIR, OMOP, Phenopackets)
• Ability to work effectively in a collaborative, interdisciplinary research environment
• Excellent problem-solving and communication skills
• Experience with functional programming languages such as Racket
• Experience with generative Al models, such as GPT-4 or Claude 3
• Familiarity with knowledge graphs and semantic web technologies (e.g., RDF, OWL, SPARQL)
• Experience with big data processing frameworks, such as Apache Spark or Hadoop
• Knowledge of cloud computing platforms, such as AWS, Microsoft Azure or Google Cloud
• Familiarity with containerization technologies, such as Docker or Kubernetes
• Experience with front-end development technologies, such as React or Angular

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