Postdoctoral Scholar in Behavioral Deep Learning
Caltech has a long tradition of innovative research initiatives that cut across traditional academic disciplines, using different scientific perspectives to solve pressing and seemingly intractable problems. In recent years, faculty from Caltech's Division of the Humanities and Social Sciences (HSS) and the Computing and Mathematical Sciences Department in the Division of Engineering and Applied Science have launched different research initiatives that combine innovations in social and computer science to study an array of social, economic, and political problems.
Working collaboratively under the supervision of Professor R. Michael Alvarez (HSS) and Professor Anima Anandkumar (CMS), the postdoctoral scholar will focus on developing machine and deep learning models that can detect toxicity in gaming behavior. The project is part of a research collaboration between Caltech and a major global gaming software company. The postdoctoral scholar will work directly with Professors Alvarez and Anandkumar, and with data science teams from industry, to use gaming data to detect toxicity in different types of data and across different gaming platforms. The candidate is expected to work closely with the gaming industry partner to understand their datasets. This unique university-industry collaboration will allow the postdoctoral scholar to gain invaluable experience working in both academic and industry settings. This collaborative project intends to develop research products that will be made accessible to the public, which will be presented at research conferences, and which will be published in peer-reviewed academic publications.
The duration of the fellowship is up to two years: an initial one-year appointment with an annual renewal contingent upon satisfactory performance. Applicants should hold or be completing a PhD in Computer Science, or a related field where they have developed extensive experience working with very large datasets and have expertise using machine and deep learning.
In addition, applicants also must have the following skills:
- Experience working in either Amazon Web Services or the Google Cloud Platforms.
- Demonstrated programming and code development skills, using deep learning frameworks like PyTorch.
- Experience in the areas of natural language processing and computer vision.
The following skills are preferred:
- Demonstrated interest working in interdisciplinary research groups, and interest in working directly with industry.
- Background working on problems relating to the detection, mitigation, and prevention of toxic behavior in large datasets.
Requirements: Position is contingent upon completion of the PhD. Interested candidates must submit a CV, a 2-3-page Research Statement, and three names of reference letter writers (as well as two letters) to email@example.com. The Research Statement should contain a section that addresses past and/or potential contributions to diversity, equity, and inclusion (e.g., mentoring activities, committee service, research, or teaching activities). A cover letter (maximum 1 page) is optional.
Applications will be reviewed starting on August 15, 2022 and will remain open until positions are filled. The deadline for the receipt of applicant materials is September 15, 2022.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, or national origin, disability status, protected veteran status, or any other characteristic protected by law.
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