Postdoctoral Research Associate –AI/ML driven Nanomaterial Synthesis
- Employer
- Argonne National Laboratory
- Location
- Lemont, Illinois
- Salary
- $69,569 + benefits
- Closing date
- Mar 28, 2021
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- Field of specialization
- Computers / Computational / Informatics, Materials
- Work Function
- Research-Basic
- Job Type
- Full time
Job Details
The Nanoscience and Technology Division/Center for Nanoscale Materials (CNM) at Argonne National Laboratory has an available postdoctoral position for the development of new nanomaterial synthesis capabilities driven by artificial intelligence and machine learning (AI/ML).
We are seeking a highly motivated and independent postdoctoral researcher to join our multidisciplinary research team to carry out research on developing an AI/ML-guided chemistry synthesis platform for autonomous nanomaterial discovery. Applicants with background in materials chemistry automation, flow chemistry, or microfluidics are strongly encouraged to apply.
The postdoctoral researcher will have access to state-of-the-art research facilities and will be a part of a world-class scientific team. Appointment is made for one year and renewable up to three years (subject to performance evaluation).
Qualifications:
Candidates should have completed a doctorate level degree (within the past three years) in chemistry, chemical engineering, materials science, or a related discipline. The following experience and skills are highly desired:
- Background in materials synthesis, flow chemistry, or microfluidic synthesis
- Synthesis/process/characterization automation driven by AI/ML
- Experience in Python programing related to instrumentation
- Excellent written and oral communication skills
- Strong skills in collaboration and ability to work in an interdisciplinary environment
Interested candidates should send a detailed curriculum vitae including a list of publications and the names and addresses of three professional references through https://www.anl.gov/hr/postdoctoral-applicants under requisition number NST 409439. For additional questions, please contact Dr. Xiao-Min Lin (xmlin@anl.gov), Dr. Elena Shevchenko (eshevchenko@anl.gov), and Dr. Ben Diroll (bdiroll@anl.gov).
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