Posted: 04/01/2024
AJO: 27428
The Laboratory for Nuclear Science (LNS) is currently engaged in the CLAS12 experiment located in Hall B at the Thomas Jefferson National Accelerator Facility, commonly referred to as Jefferson Lab, situated in Newport News, Virginia. Led by Professor Richard Milner, the MIT-CLAS12 group is dedicated to determining absolute cross-sections for deeply virtual exclusive processes. Moreover, the group is actively involved in high-level analysis aimed at studying Generalized Parton Distributions (GPDs) to deepen our understanding of the proton 3-D imaging and advance research into its gravitational structure. The position entails collaborating with CLAS12 colleagues at Jefferson Lab on data analysis, as well as the extraction and publication of scientific findings.
Review of applications will begin at the time of receipt and the position will remain open until filled. To ensure full consideration, candidates should apply by June 1, 2024. Applicants are asked to submit a cover letter, curriculum vitae, and brief statement of research interests and experience via both the AJO website (in a single pdf) and directly to Professor Richard Milner at milner@mit.edu. Please also arrange for three letters of recommendation to be sent to Professor Milner via email.
Applicants should hold a PhD in experimental nuclear or particle physics, along with experience in high-level data analysis. Proficiency in advanced computational skills, particularly in Artificial Intelligence (A.I) and Machine Learning (M.L), would be advantageous.
LNS benefits from a diverse and engaged workplace and seeks to further enhance our community by employing individuals from varied backgrounds. LNS actively supports MIT’s commitment to advancing a respectful and caring community that embraces diversity and empowers everyone to learn and do their best.
MIT is an equal employment opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, sex, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, ancestry, or national or ethnic origin.
