Pre-Doctoral Technical Associate - Johan Chu

Description

Professor Johan Chu (https://mitsloan.mit.edu/faculty/directory/johan-chu) is seeking one or more highly skilled, collaborative, and motivated individuals to work as full-time research assistants (predocs). The position(s) will be based at the MIT Sloan School of Management in Cambridge, MA. The duration of the position(s) is at least one year, with a flexible start date. The selected candidate(s) will gain exposure to and training in a broad set of research approaches and methodologies useful for applying to graduate programs in Management, Sociology, and Political Science. 

Predoc associates will be fully integrated into the local research community. They will interact with research scientists, post-docs, faculty, and other PAs. The faculty will provide mentorship and support the PA through the process of preparing for and applying to PhD programs. The chosen candidates will also have the opportunity to take courses and attend seminars at MIT.

Please visit (http://predoc.org) for more information about what a predoc is, and to find other predoctoral opportunities across a consortium of universities and research institutions.

Qualifications

The position is ideally suited for candidates planning to pursue a PhD degree in System Dynamics, Macro-Organizational Behavior, Economic Sociology, or Strategy. Data wrangling, computational, and quantitative skills are required--and will be honed during the predoc term. Quantitative work will include acquiring and processing archival data, applying machine learning to generate insights from data, regression/causal inference, and simulation. Verbal and written communication skills are also required.

The ideal candidate will have:

• Completed or be on their way to completing a 4-year undergraduate degree and/or Master's degree. The field can be any that involved rigorous involvement with data, e.g. Machine Learning/Data Science, Computer Science, Physics, Applied Math, Economics, Political Science, Sociology, Management, etc.
• A strong quantitative background with comfort in processing data and writing code, ideally in Python and/or C
• Machine learning engineering experience
• Past experience as a research assistant and/or independent work on data-intensive projects
• Proven ability to independently solve challenging problems
• Diligence and a love for precision and detail in, e.g., getting data correct
• Execution ability (e.g. delivering deliverables on time, overcoming obstacles, creating structures)
• Excellent communication skills (e.g. in reading and writing academic prose; writing clear research logs)
• The ability to read and write Korean and/or Vietnamese is not required, but would be a plus

Visa sponsorship is not available for this position. Candidates should have authorization to work in the US for the duration of the appointment.

Application Instructions

• One-page cover letter describing your motivation for undertaking the pre-doc position, previous relevant coursework, research experience, and future academic and/or research aspirations
• CV
• Academic transcript (unofficial is fine)
• Writing sample. This can be any research paper, term paper, or other document that you think best reflects your abilities

Applications will be reviewed on a rolling basis. Shortlisted applicants will be asked to participate in an interview and coding exercise. We will only notify shortlisted applicants.

Equal Employment Opportunity Statement

Massachusetts Institute of Technology 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. MIT’s full policy on Nondiscrimination can be found here.

Background Check Policy
Employment is contingent upon the completion of a satisfactory background check, including possible verification of any findings of misconduct (or pending investigations) from prior employers.