Staff Scientist

Department

PME Xu Lab About the Department

The Pritzker School of Molecular Engineering (PME) was established in May 2019 and evolved from the Institute for Molecular Engineering, which was founded in 2011. The PME integrates science and engineering to address global challenges from the molecular level up. The PME’s rigorous academic and research programs are made possible through the University of Chicago’s unique partnership with Argonne National Laboratory. The Pritzker School of Molecular Engineering is the first new school at the University of Chicago in three decades and the first school in the nation dedicated to molecular engineering. In the next phase of growth as a School, the PME will continue to expand its team of world-class faculty researchers and empower students from diverse backgrounds to collaborate with faculty in cutting-edge facilities. The PME aims to bring solutions for urgent societal problems to the forefront, while training the next generation of scientific leaders and entrepreneurs.

Job Summary

We are looking for a highly motivated Staff Scientist with expertise in designing automated lab for material discovery, and to work closely with faculty and researchers at the University of Chicago. The successful candidate will play a key role in the PoLARIS project, which is designed to make advanced polymer research faster, more accessible, and more reproducible. The research project will connect AI, robotics, specialized instruments, and data infrastructure into a cloud laboratory that researchers can access remotely and in collaboration with researchers at the University of Chicago and Argonne National Laboratory.

Responsibilities

• Facilitates and promotes advanced technical/scientific research projects, including automated workflow, and data analysis. Recognizes the need for innovation and develops or incorporates advances in research concepts to help disseminate results.

• Develops, applies, documents, and maintains computational tools, both for use and to support experimental colleagues without formal automation training.

• Develops customized automated platform and method supporting new kinds of assays and experiments. Understands the analytical needs of new experiments, working closely with wet-lab experimental biologists.

• Implements and optimizes successful algorithms and methods to be shared for use by the broader community.

• Develops figures and reports that provide transparency into the data quality and characteristics and automates the production of such reports as routine components of automated workflow pipelines.

• Reports data to supervisor and team, attends team meetings to share results, plan projects, and experiments, and ensures that projects support current team goals.

• Maintains and organizes automated hardware infrastructure and resources.

• Contributes to the generation of protocols, publications, and intellectual property.

• Reviews laboratory protocols and training on new techniques. Manage complex data sets for research.

• Trains new laboratory personnel.

• 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 2-5 years of work experience in a related job discipline. Certifications:

• Preferred Qualifications

Education

• Doctoral degree in chemistry, engineering, or related field.

Experience

• Postdoc experience, a minimum of three years of significant work experience after the doctorate.

• Possess experience in a research laboratory, preferably in an independent project.

• Practical experience in data analysis, preferably in an independent project in an academic research laboratory setting.

• Background in statistics and machine learning.

Technical Skills or Knowledge:

• Strong computer skills, including calendaring, document management, such as Dropbox and Box, etc., word processing, database management, and spreadsheet skills.

• Knowledge of statistical/analytical software.

• Advanced knowledge of computer programming and coding languages.

• Preferred Competencies

• Excellent communication skills to interact professionally with all levels of staff and with external contacts in a fast-paced environment.

• Excellent organization and time management skills.

• Demonstrated problem-solving, organization and coordination skills.

• Demonstrated excellent oral and written communication skills.

• Excellent time management skills to handle multiple, concurrent tasks within deadlines with minimal supervision.

• Prioritize urgent tasks while ensuring established deadlines are met.

• Flexible and adaptable to changes in workflow and procedures.

• Application Documents

• Resume/CV (required)

• The University of Chicago uses AI-assisted tools to streamline and augment some recruitment processes; however, AI is not used to make hiring decisions.

• Job Family

• Research

• Role Impact

• Individual Contributor

• Scheduled Weekly Hours

• 40

• Drug Test Required

• No

• Health Screen Required

• No

• Motor Vehicle Record Inquiry Required

• No

• Pay Rate Type

Salary

FLSA Status

Exempt Pay Range

$90,000.00 - $100,000.00 Benefits Eligible

Yes The University of Chicago offers a wide range of benefits programs and resources for eligible employees, including health, retirement, and paid time off. Information about the benefit offerings can be found in the

Benefits

• Guidebook.

• Posting Statement

• The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

• All offers of employment are contingent upon a background check that includes a review of conviction history. A conviction does not automatically preclude University employment. Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

• The University of Chicago's Annual Security & Fire Safety Report (Report) provides information about University offices and programs that provide safety support, crime and fire statistics, emergency response and communications plans, and other policies and information. The Report can be accessed online at: securityreport.uchicago.edu. Paper copies of the Report are available, upon request, from the University of Chicago Police Department, 850 E. 61st Street, Chicago, IL 60637.