Staff Scientist

Staff Scientist

The Staff Scientist will conduct original research modeling immune-microbe interactions using computational and machine learning approaches. The role emphasizes exploratory work at the intersection of immunology and AI. The Staff Scientist will work in a collaborative environment with computational and experimental investigators in the Institute for Population and Precision Health (IPPH) and at the Laboratory for Computational Immunology, University of Chicago, and partner institutions.

Responsibilities:

• Develop and apply computational and machine learning methods to model host immune responses to microbial communities, integrating microbiome and protein-level analyses.
• Pursue independent lines of inquiry at the intersection of microbial proteins, immunology, and AI, generating new hypotheses and innovative research directions.
• Partner with wet-lab teams to connect computational predictions with microbiome and immunological data, facilitating cross-disciplinary insights and translational outcomes.
• Promote open science principles, share code and data, and engage with the scientific community via conferences, seminars, and collaborative initiatives.
• Serves as a resource for collecting data and performing analysis. Facilitates and promotes a research project by providing scientific or intellectual information.
• Creates first drafts for scientific writing and publications, including protocols and grants.
• Performs other related work as needed.

Minimum Qualifications:

• Education:
  
  Minimum requirements include a PhD in related field.
• Work Experience:
  
  Minimum requirements include knowledge and skills developed through 5-7 years of work experience in a related job discipline.

Preferred Qualifications:

• Education:
  
  Ph.D. in Computational Biology, Bioinformatics, Computer Science, or a closely related quantitative field.
• Experience:
  
  At least one year of research experience in machine learning applied to microbiology, protein science or related biological problems.

Preferred

Competencies:

• Demonstrated experience applying computational and machine learning methods to microbiome data and protein sequence or structural data.
• Proficiency with the Python scientific and ML ecosystem and experience on Linux HPC / SLURM clusters or cloud environments.
• Ability to conduct independent research, mentor junior lab members, and communicate results clearly in writing and in presentations.
• Familiarity with current trends in AI and biological data sciences.
• Commitment to ethical research practices, data integrity, and responsible AI principles.
• Outstanding organization, analytic, and communication (oral and written) skills.
• Ability to work independently, as part of a team, and collaboratively, depending on the job needs.
• Attention to detail and problem-solving skills.

Working Conditions:

• The work will take place primarily within an office or dry lab.
• Weekend or evening hours may be required to complete project timelines.

Application Documents:

• Resume (required)
• Cover Letter (preferred)

Job Family:
Research

Role Impact:
Individual Contributor

Scheduled Weekly

Hours:

40

Pay Range: $80,000.00 - $

Benefits Eligible:
Yes