AI for Science Research Fellow (PhD Candidate, Part-Time)

Chemical Abstracts Service

Columbus (OH)

On-site

USD 41,000 - 69,000

Part time

14 days+
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Job summary

Chemical Abstracts Service (CAS), the scientific information solutions division of the American Chemical Society, seeks a part-time PhD in AI Research for Science for a 6-month placement at our Columbus, Ohio headquarters.

The role targets PhD students in chemical, biological, biomedical, physical, or materials sciences to apply AI methods to challenging problems, under mentorship from CAS experts, contributing to innovation within the CAS product portfolio.

Qualifications

  • Currently pursuing a PhD in a relevant discipline (chemistry, biology, biomedical science, physics, materials science, or cheminformatics).
  • Strong interest in applying AI/ML methods to scientific problems.
  • Proficiency with Python or R and SQL.
  • Ability to work through ambiguous technical problems with mentorship.
  • Demonstrated analytical, multi-tasking, problem solving and planning skills.

Responsibilities

  • Contribute to innovation and discovery efforts in AI for science.
  • Conduct literature review and technical landscape analysis.
  • Design, build, and iterate prototypes or models.
  • Validate outputs with CAS domain experts.
  • Document methodology, results and recommendations in a formal technical report.
  • Present findings to the CAS technical team.
  • Perform other duties as assigned.

Skills

Python
R
SQL
AI concepts
Analytical skills
Communication
Independent work

Education

PhD student in a relevant discipline

Job description

Chemical Abstracts Service (CAS), the scientific information solutions division of the American Chemical Society, seeks a part-time PhD in AI Research for Science for a 6-month placement at our Columbus, Ohio headquarters.

The role targets PhD students in chemical, biological, biomedical, physical, or materials sciences to apply AI methods to challenging problems, under mentorship from CAS experts, contributing to innovation within the CAS product portfolio.

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