美国哈佛商学院博士后职位—计算和数学科学

美国哈佛商学院博士后职位—计算和数学科学

哈佛商学院是美国哈佛大学下设学院，全球最有名的商学院。建于1908年的哈佛商学院（Harvard Business School，简称HBS）是美国培养企业人才最著名的学府，被美国人称为培养商人、主管、总经理的“工厂”，美国许多大企业家和政治家都在这里学习过。在美国500家最大公司里担任最高职位的经理中，有1/5毕业于这所学院。哈佛商学院的工商管理硕士学位（Master of Business Administration，简称MBA）成了权力与金钱的象征，成为许多美国青年梦寐以求的学位。

哈佛商学院在2018-2022年UTD全球商学院科研排名百强榜中位列全球第3位。

Postdoctoral Fellow - Laboratory for Innovation Science at Harvard, Computational & Mathematical Sciences

Harvard Business School

Position Description        

The Digital Data Design (D^3) Institute and the Laboratory for Innovation Science at Harvard (LISH) seek enthusiastic Postdoctoral Fellows skilled in Natural Language Processing (NLP), Artificial Intelligence, and Machine Learning. As part of an interdisciplinary research team dedicated to advancing innovation science, the fellows will apply quantitative and experimental field methods to address challenges faced by partnering organizations.

The Postdoctoral Fellows will play a pivotal role within the LISH Lab Team, collaborating with Harvard Business School (HBS) faculty and LISH researchers to leverage data in advancing social science research across business, management, digital transformation, data science, and artificial intelligence. Business, the global economy, and societies around the world are facing dramatic upheaval as a result of rapid technological change driven simultaneously by digitization, the application of artificial intelligence and machine learning to all facets of company, economic, and human data, and a new emphasis on the importance of design and innovation on value creation for stakeholders. Postdoctoral Fellows at D^3 will engage in research projects spanning Business Model Transformation, Operating Model Transformation, Organizational and Workforce Transformation, Performance and Metrics, Data Privacy and Transparency, and Societal Impact. We seek candidates with experience in one or more of the following areas: causal inference, econometrics, experimental design and analysis, or the analysis of complex data, including networks. The ideal candidate will have a robust background in data science, particularly with an emphasis on generative AI. They will apply their expertise in quantitative methods, data science techniques, and language models to effectively analyze and manage research data. There are no teaching obligations for these positions.

Basic Qualifications        

A Ph.D. or equivalent degree in Computational & Mathematical Sciences for the statistics, computer science, information systems or operations. All degree requirements must be satisfied prior to the fellowship start date.

PLEASE NOTE: 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 institution’s Registrar stating all requirements for the degree have been successfully completed and should verify the date the degree has been conferred. No exceptions.

Additional Qualifications        

Special Instructions        Interested in Learning More?

Join us for a virtual Postdoc Info Session on Thursday, December 19th 2:30 PM – 4:30 PM, more information including Zoom link seen here: https://d3.harvard.edu/postdoc-info-session/

Application Details:

Applications will be accepted until positions are filled.

Please apply here via the Harvard system. Please do not contact lab faculty; if you have any questions, please contact d3@harvard.edu.

All applications must include the following:

•       Curriculum vitae

•       Statement of research

•       Two representative publications

•       Two letters of recommendation

Candidates may be asked to undergo an assessment as part of the interview process.

Additional Information:

These are term positions starting July 2024 (start date flexible) through June 30, 2025, with the possibility of renewal based on funding and performance. Relocation funding not provided.

This role is offered as a hybrid (some combination of onsite and remote) where you are required to be onsite at our Boston, MA based campus. Specific days and schedule will be determined between you and your manager.

Please note that we will be conducting interviews virtually (phone and/or Zoom) for selected candidates.

Culture of Inclusion: The work and well-being of HBS is profoundly strengthened by the diversity of our network and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. Explore HBS work culture at https://www.hbs.edu/employment/.

Commitment to Equity, Diversity, Inclusion, and Belonging

Harvard University views equity, diversity, inclusion, and belonging as the pathway to achieving inclusive excellence and fostering a campus culture where everyone can thrive. We strive to create a community that draws upon the widest possible pool of talent to unify excellence and diversity while fully embracing individuals from varied backgrounds, cultures, races, identities, life experiences, perspectives, beliefs, and values.

EEO Statement

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.

Contact Information       Harvard Business School

Soldiers Field Road

Boston, MA 02163

Contact Email  afulmine@hbs.edu

Equal Opportunity Employer We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions or any other characteristic protected by law.

Minimum Number of References Required  2

Maximum Number of References Allowed    4

Keywords        

Supplemental Questions

Required fields are indicated with an asterisk (*).

Applicant Documents

Required Documents

1.      Curriculum Vitae

2.      Statement of Research

3.      Publication

4.      Publication 2

Optional Documents

1.      Transcript

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