Research Technician at The University of Chicago in Chicago, IL
- Company: The University of Chicago
- Location: Chicago, IL
- Job type: full time
- Workplace: onsite
- Posted: 2026-09-28
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Job description
Department PSD Enrico Fermi Institute: Administration About the Department The Enrico Fermi Institute is an interdisciplinary research unit within the Division of Physical Sciences of the University of Chicago. The Institute's activities include the following: string theory and theoretical high-energy physics, experimental high-energy physics, theoretical astrophysics and cosmology, experimental particle astrophysics, infrared and optical astronomy, cosmic microwave background observations, general relativity, and gravitational waves, and cosmochemistry. Job Summary The Research Technician will work with the University of Chicago experimental particle physics group on the assembly, testing, and quality control of silicon pixel detector modules for the ATLAS experiment at CERN's Large Hadron Collider. The position will be based primarily at Argonne National Laboratory and will support the production of detector modules for the upgraded ATLAS Inner Tracker (ITk). The successful candidate will work closely with University of Chicago researchers and the ATLAS pixel team at Argonne, as well as collaborators at institutions across the U.S. and internationally. This position is intended for a post-baccalaureate researcher. The position provides an opportunity to gain substantial experience in experimental particle physics and detector instrumentation while contributing directly to the construction of a major international scientific instrument. The successful candidate will receive hands-on training in all tasks. This position is grant-funded and expected to last approximately one year, with the possibility of future renewal based on project or grant funding. Responsibilities Support assembly and testing of ATLAS ITk pixel modules at Argonne. Receive, inspect, and record detector components and materials. Perform basic, metrology and electrical, measurements of components and assembled modules. Carry out electrical and quality-control tests using standard procedures. Assist with module processing steps such as masking, de-masking, and parylene coating. Prepare modules and documentation for shipment. Enter and check production and test data in databases. Maintain production records. Work with the team to support efficient production. Help identify and troubleshoot issues during assembly and testing. Attend team meetings and training sessions. Follow all lab safety, cleanroom, and security rules. Collects and enters data. Assists in analyzing data. Assists with preparation of reports, manuscripts and other documents. Provides routine or standardized laboratory duties by collecting data in support of research projects under direct supervision. Performs other related work as needed. Minimum Qualifications Education: Minimum requirements include vocational training, apprenticeships or the equivalent experience in related field (not typically required to have a four-year degree). Work Experience: Minimum requirements include knowledge and skills developed through Certifications: --- Preferred Qualifications Education: Bachelor’s degree in Physics, Engineering or a related field, or at least two completed years in such a program. Recent bachelor's degree graduates interested in pursuing graduate study or a career in experimental physics, detector instrumentation, or engineering are especially encouraged to apply. Experience: Laboratory or experimental research experience with electrical measurements, lab equipment, or electronics. Experience in a cleanroom or controlled lab environment, with particle physics or silicon detector work is a plus. Experience assembling small components or precision mechanical work. Experience using spreadsheets, databases, or similar tools for data entry and analysis. Experience with programming (e.g., Python, C++), Linux/Unix, or similar tools. Preferred Competencies Attention to detail and commitment to accurate, reliable work. Good organization and data management skills. Basic quantitative and data analysis
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