Postdoctoral Fellow- AI & Data Science Operations (DSOps) Lab- Digital, Data, and Design Institute, Harvard University
Location: Cambridge, Massachusetts
Internal Number: 12137
School: Harvard Business School
The Digital, Data, and Design (D^3) Institute at Harvard is accepting applications for multiple The Digital, Data, and Design (D^3) Institute at Harvard is accepting applications for multiple postdoctoral fellows for academic year 2023-2024 to work on research activities at our research labs. D^3 launched in the summer of 2022 with 12 labs working on research at the intersection of academia and practice. For more information on D^3, please visit https://d3.harvard.edu.
The postdoctoral fellows will work under the direct supervision of faculty Principal Investigators and the Senior Associate Director, Lab Operations. They will work closely with the lab manager and research associate(s) at each lab. D^3 is looking for candidates with diverse backgrounds and/or new perspectives. There are no teaching requirements for these open positions.
As part of the Laboratory for Innovation Science at Harvard (LISH), the AI & Data Science Operations (DSOps) Lab, led by HBS Professors Iavor Bojinov and Edward McFowland III, is seeking a Postdoctoral Fellow. The lab focuses on how companies develop data science capabilities throughout the entire pipeline, starting with the management questions, data collection and analysis phases, and final decision-making. Of particular interest are topics around building a data-first company, developing and deploying state-of-the-art causal inference and predictive algorithms, using experimentation platforms to drive organizational innovation, and other relevant research and managerial questions. The lab's projects will be situated in research settings that are high-stakes and managerial in nature, where research questions and algorithmic developments focus on the intersection of joint human and algorithmic decision-making. Finally, we also explore how data science enables efficacy and scalability of new data-driven and algorithm-supported operating models, understanding if or when it is appropriate for algorithms to operate autonomously with (or without) human oversight.
The antecedents and consequences of human trust in algorithmic recommendations of managerial decisions,
Detecting and overcome biases in algorithmic and human decision-making,
Development of novel algorithms for causal inference
The design and deployment of an experimentation platform and its impact on innovation.
The successful candidates will leverage their strong technical background and communication skills to engage and contribute to collection projects (some of which they will lead) in all stages of the research, including the design, theoretical analysis, implementation, evaluation, and demonstration on real-world datasets.
A Ph.D. or equivalent degree in computer science, statistics, economics, management science, information systems, operations, or other related quantitative and/or social science domains. PLEASENOTE: If you have obtained your Ph.D. in the past 12 months you must be able to provide a certificate of completion from the degree-granting institution OR a letter from the institute's registrar stating all requirements for the degree have been successfully completed and should verify the date the degree has been conferred. No exceptions.
Proficiency in computer programming (Python, R)
Strong team player with excellent communication skills
Experience with experimental design
Laura Kelley, Associate Director, Research Staff Services Harvard Business School Soldiers Field Road Boston, MA 02163
Applications will be accepted until the position is filled. Please apply here via the Harvard system. Please do not contact lab faculty; if you have any questions, please contact [email protected].
All applications should include the following:
Link to Github account and/or any software developed
Copy of academic records (official records are acceptable)
2-page research statement describing prior research experience and future research plans
Two representative publications (preprints are acceptable)
Three letters of recommendation.
Candidates may be asked to undergo an assessment as part of the interview process.
This is a term position through June 30, 2024, with the strong possibility of renewal based on funding and performance. Relocation funding not provided.
The University requires all Harvard community members to be fully vaccinated against COVID-19 and remain up to date with COVID-19 vaccine boosters, as detailed in Harvard's Vaccine & Booster Requirements. Individuals may claim exemption from the vaccine requirement for medical or religious reasons. More information regarding the University's COVID vaccination requirement, exemptions, and verification of vaccination status may be found at the University's
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