We are seeking an AI Research Specialist in Computational Biology to join our efforts, working at the intersection of AI-driven data science and experimental biology. The successful candidate will carry complex, heterogeneous biological datasets from analysis and interpretation through to the interactive tools that enable scientists and autonomous systems to act on the results.
The scope of this position is intentionally broad. Rather than owning a narrow stage of an established pipeline, the successful candidate will lead end-to-end projects, moving between analysis, engineering, and interface design as each project requires. Representative work includes mapping functional biological terms and ontologies to one another using data science techniques and surfacing the results in purpose-built visualizations; developing dashboards used by our group and our external collaborators to monitor data streaming from our automated laboratory, backed by an API that allows AI agents to engage with and autonomously drive the lab; and performing multimodal analysis of video captured from microfluidic devices during live experiments.
Fluency in co-working with AI is a defining requirement of this role. The successful candidate will use large language models as a core element of their daily practice, enabling a single scientist to deliver at a scale that would otherwise require a team. Demonstrated ability to direct, evaluate, correct, and build upon AI-generated work is essential.
Core Responsibilities:
- Lead complex biological data analysis projects from framing through delivery, applying data science and AI techniques to extract meaningful patterns, trends, and variables from large and heterogeneous datasets.
- Design and build interactive dashboards that allow scientists to visualize, explore, manipulate, and curate biological data.
- Build and maintain the full-stack platforms and backend infrastructure that support those dashboards.
- Develop APIs and data pipelines that expose laboratory data and analysis results to both human collaborators and autonomous AI systems.
- Apply embedding-based approaches - across natural language, biological sequence, and other modalities - to problems where they offer analytical leverage.
- Work directly with experimental scientists to understand their goals, elicit requirements, and translate them into working tools and analyses.
- Communicate complex results to technical and non-technical audiences in a form they can grasp quickly.
Position RequirementsRequired:
- RD!: Minimum of a Bachelor's degree in computational biology, bioinformatics, data science, computer science, or a closely related field.
- Biology domain expertise: A background in biology sufficient to reason independently about biological data and to engage substantively with experimental scientists.
- Python: Demonstrated proficiency as a primary working language for data science and application development.
- Data science.: Experience analyzing complex, heterogeneous datasets to identify important trends, relationships, and variables of interest.
- Visual dashboard development: Demonstrated experience building dashboards for data analysis, visualization, and curation by human users.
- Backend and API development: Experience building the backend services and APIs that support data-facing applications.
- Data embeddings: A working understanding of how embedding technology functions and the ability to apply it creatively across domains - including language embeddings and protein sequence embeddings.
- Co-working with AI: Practical experience using large language models as a primary tool for building software and conducting analysis.
- Collaboration and communication: The ability to present complex results clearly and quickly to varied audiences, and to work with scientists to elicit and understand their underlying needs.
- Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork.
Preferred:
- Experience with multimodal data analysis on biological datasets, working across data modalities (e.g., imaging or video alongside structured or sequence data).
- Experience with laboratory automation, instrument data streams, or agent-driven experimental systems.
- Prior work supporting research groups or scientific collaborators in a service or partnership capacity.
- Familiarity with genome annotation, metabolic modeling, or systems biology (e.g., KBase, ModelSEED, KEGG).
Job FamilyResearch Development (RD)
Job ProfileComputational Science 1
Worker TypeLong-Term (Fixed Term)
Time TypeFull time
The expected hiring range for this position is $78,505.00 - $122,467.41.
Please note that the pay range information is a general guideline only. The pay offered to a selected candidate will be determined based on factors such as, but not limited to, the scope and responsibilities of the position, the qualifications of the selected candidate, business considerations, internal equity, and external market pay for comparable jobs. Additionally, comprehensive benefits are part of the total rewards package.
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As an equal employment opportunity employer, and in accordance with our core values of impact, safety, respect, integrity and teamwork, Argonne National Laboratory is committed to a safe and welcoming workplace that fosters collaborative scientific discovery and innovation. Argonne encourages everyone to apply for employment. Argonne is committed to nondiscrimination and considers all qualified applicants for employment without regard to any characteristic protected by law.
Argonne employees, and certain guest researchers and contractors, are subject to particular restrictions related to participation in Foreign Government Sponsored or Affiliated Activities, as defined and detailed in United States Department of Energy Order 486.1A. You will be asked to disclose any such participation in the application phase for review by Argonne's Legal Department.
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