Publisher
source

Feng Li

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2 days ago

Postdoc Opportunity in Computing, Forecasting and Learning with Massive Machines at Peking University Peking University in China

Degree Level

Postdoc

Field of study

Computer Science

Funding

Full funding available
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Country

China

University

University of Pisa

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Keywords

Computer Science
Mathematics
Forecasting
Management
Management Science
Statistics
Post Doc
Machine learning
compututional

About this position

Guanghua School of Management at Peking University is seeking very strong postdoctoral candidates for the Guanghua Thought Leadership Program.

The post is associated with Feng Li, Associate Professor at Guanghua School of Management, Peking University, with research interests in computing, forecasting, and learning with massive machines. This makes the opportunity especially relevant for applicants with backgrounds in Computer Science, Statistics, Mathematics, and related quantitative fields.

Funding and benefits: the successful candidate will receive a competitive annual salary paid monthly for up to 48 months. The package also includes housing provident fund, endowment insurance, public medical care, and other standard benefits. There is also an opportunity to apply for other teaching and research positions depending on hiring needs.

Eligibility highlights: the post explicitly asks for very strong postdoc candidates. No detailed degree, language test, or GPA requirements are stated in the post itself.

How to apply: interested candidates should review the full English or Chinese details via the linked pages and contact Feng Li directly by email if they are interested in working with him.

Institution: Peking University, China.

Funding details

Full funding including tuition fees and living expenses is available for this position. The scholarship covers all educational costs and provides a monthly stipend.

How to apply

Please submit your application including a cover letter, CV, academic transcripts, and contact information for two references. Applications should be sent via the online portal before the deadline.

More information can be found here

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