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Research Associate in Cookpad Networks

University of Bristol - Department of Engineering Mathematics

Location: Bristol
Salary: £33,199 to £37,345
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 22nd March 2019
Closes: 21st April 2019
Job Ref: ACAD103858

Contract Type: Fixed Term Contract

Work Hours: 35.0 Hours per Week

Division/School: School of Computer Science, Electrical and Electronic Engineering and Engineering Maths

Based within the Department of Engineering Mathematics at the University of Bristol, with Dr. Naoki Masuda you will analyse data provided by Cookpad LTD, the funder of the present project. The job is for 6 months starting from 1 August 2019 (till the 31st of January 2020) and is a replacement of the previous job holder who will be working till summer 2019.

We are looking for a highly-motivated, self-driven PhD in network science, complexity sciences, computer science, applied mathematics, other data-science related disciplines, or a related field. Some background in either network science or related areas (e.g. social media data analysis, econophysics, CS, applied mathematics with some experiences of data analysis) will be considered as a plus. Skills in Python or MATLAB, C/C++ or a similar programming language will also be considered as a plus.

You will handle time-stamped data containing logs of communication among users in different modes, users’ other behaviour on the platform, categorisation of the posted recipes and so on. All the data are anonymised. Then, we will construct networks of e.g. users, both static networks and temporally varying networks, and submit them to various types of network analysis (e.g. community detection, core-periphery structure, centrality, bursts, temporal networks, multilayer networks) and other types of analysis (e.g. standard tools from machine learning) to derive knowledge. We may also simulate user dynamics (e.g., propagation of information on networks of users; users’ entry to and exit from the platform) to investigate possible scenarios and make predictions.

Cookpad is the largest cooking recipe-sharing community in the world providing an online platform with about 100m monthly unique users worldwide. They are operating the service in more than 60 countries ( The mission of Cookpad is “make everyday cooking fun”. They are committed to build a better world through encouraging more people to cook. Everyday home cooking has a profound impact on ourselves and the world around us; it makes us healthy, connects us with our friends and family and makes our environment sustainable. Through solving problems related to everyday cooking, the company intends to help people live happier and healthier lives.

Cookpad would like to solve questions such as: Who are key users who channel viral information spreading and cozy communication on the platform? How should we determine such key users? Why do some user communities grow over time whereas others do not? How different are the networks in different countries and language groups?

Using large data sets provided by the company, we will tackle these issues using analysis tools from network science, machine learning and/or computational social science.

For informal enquires please contact Dr. Naoki Masuda


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