Argonne National Laboratory is seeking a highly motivated Post-Doctoral Researcher to develop and advance the IDeA co-scientist project. The role involves creating AI-powered autonomous research assistants to transform biological research through intelligent systems that collaborate in the scientific process.
Responsibilities
- Design and implement generative AI models and agentic systems capable of scientific reasoning and hypothesis generation in biological contexts
- Develop and integrate tool-calling frameworks that enable AI agents to interact with bioinformatics software, computational modeling platforms, databases, and experimental systems
- Build scalable architectures for multi-agent systems that can coordinate complex research workflows across computational and experimental domains
- Create feedback mechanisms that allow AI co-scientists to learn iteratively from experimental results, simulation outputs, and literature
- Implement prompt engineering strategies, retrieval-augmented generation (RAG), and knowledge graph integration for scientific reasoning
- Develop evaluation frameworks and benchmarks to assess the performance of AI co-scientists in biological discovery tasks
- Collaborate with experimental biologists, computational scientists, and engineers to identify use cases and validate AI-driven discoveries
- Optimize system performance for deployment on high-performance computing infrastructure and cloud platforms
- Publish findings in high-impact journals and present research at leading AI and computational biology conferences
- Contribute to open-source tools and frameworks that advance the broader AI-for-science community
Skills
- Completed or Soon-to-be-completed Ph.D. within the last 0-5 years in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Bioinformatics, or a related field
- Strong programming skills in Python, with experience in AI/ML frameworks (PyTorch, JAX, Hugging Face Transformers)
- Experience developing or working with large language models (LLMs), agentic systems, or autonomous AI agents
- Demonstrated ability to integrate AI systems with external tools, APIs, databases, or software packages
- Understanding of biological systems, bioinformatics workflows, or computational biology applications
- Strong problem-solving skills and ability to work on open-ended research questions
- Excellent communication skills and ability to work collaboratively in interdisciplinary teams
- Strong publication record or demonstrated potential in relevant fields
- Ability to model Argonne's core values of impact, safety, respect, integrity and teamwork
- Experience with agentic AI architectures, including ReAct, Chain-of-Thought reasoning, or multi-agent systems
- Familiarity with tool integration frameworks such as LangChain, LlamaIndex, AutoGPT, or similar platforms
- Knowledge of retrieval-augmented generation (RAG), vector databases, and knowledge graph integration
- Background in systems biology, genomics, protein engineering, or drug discovery
- Familiarity with high-performance computing environments and scalable distributed systems
- Knowledge of bioinformatics tools and databases (BLAST, UniProt, PDB, KEGG, etc.)
- Experience with API development, microservices, and/or container architectures (Singularity)
Benefits
- Competitive salary
- Professional development opportunities
- Funding for conference travel
Company Overview
Argonne National Laboratory conducts researches in basic science, energy resources, and environmental management. It was founded in 1946, and is headquartered in Lemont, Illinois, USA, with a workforce of 1001-5000 employees. Its website is http://www.anl.gov/.
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