job: PhD candidate in data science and artificial intelligence for digital food environments, Wageningen University, the Netherlands

Application deadline is 20 February 2023. The first job interviews will take place on 7 March 2023.
Complete details are here: PhD candidate in data science and artificial intelligence for digital food environments - WUR<https://www.wur.nl/en/vacancy/phd-candidate-in-data-science-and-artificial-intelligence-for-digital-food-environments.htm>


You are welcome to apply or share with potential interested candidates - thank you!


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Do you want to apply your passion for data science and artificial intelligence on healthy food environments? Are you a person who likes to work interdisciplinary at the interface between computer science and public health nutrition? Do you get excited to develop and advance methodologies to gain better insight into digital food environments? Then we are looking for you!

Unhealthy diets are a major risk factor for non-communicable diseases and deaths globally. Our so-called 'food environment' is a key driver of unhealthy diets: it is easier to choose unhealthy foods over healthy foods. To illustrate, 80% of the products offered and promoted by Dutch supermarkets do not contribute to a healthy diet. Also, neighborhood fast food density increased over the past decades and has been positively associated with overweight and chronic diseases. More recently, the digital transition transformed and disrupted our food environment and the way we shop for food.

Smart technology has increased consumers’ access to grocery and meal delivery services, the latter often via third party platform-to-consumer delivery services. These services have enabled access to a greater number of restaurants and expanded meal options accessible compared to brick-and-mortar food outlets in the neighborhood. At the same time there has been a shift from traditional marketing (e.g., via TV, packages) towards digital marketing, using a range of new marketing channels (e.g., social media, games) and strategies (e.g., personalized persuasion techniques, influencers). Although the concept of the digital food environment has already been recognized in the literature, little is known about the characteristics and omnipresence of online food availability and food promotions, and in turn, how this could affect eating behavior and public health.

At this point in time, public health researchers often manually collect and analyze digital food environment data or incorporate rather simple web-scraping techniques to obtain data. Because of this, current evidence is relatively static and limited, given the large size and dynamic nature of digital food environments. Development of new artificial intelligence and data science methods that employ structured and semi-structured (open and closed) data, various web application programming interfaces, unstructured data, crowdsourcing, etc. becomes a necessity and creates innovation, feasibility and scalability. Furthermore, as digital environments are very context-dependent, adequate artificial intelligence and data science methods that integrate and reason with the context information in such setting are yet to be designed and developed.

As part of this PhD project you will:

  *   Create, improve and develop data science and artificial intelligence techniques and tools to define and understand digital food environments, for example data aggregation and knowledge graph generation; semantic modeling and information extraction; decision making with hybrid reasoning;

  *   Apply these techniques and tools to collect, clean, process and monitor features of digital food environments including food availability and food promotions of different online channels (meal delivery platforms, social media (algorithms) and to visualize outcomes attractively (e.g., via digital dashboard);

  *   Write scientific papers in high-impact scientific journals and conferences in the field of applied computer science as well as public health nutrition sciences;

  *   Present your work at internal meetings and at (inter)national conferences;

  *   Collaborate within an interdisciplinary team (computer science, public health nutrition, consumer sciences);

  *   Write a doctoral dissertation.

Apply online: https://www.wur.nl/en/vacancy/phd-candidate-in-data-science-and-artificial-intelligence-for-digital-food-environments.htm


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Prof. Dr. Anna Fensel

Full Professor, Personal Chair in Artificial Intelligence and Data Science


Wageningen University and Research

The Netherlands

www.wur.eu<http://www.wur.eu>

Email: anna.fensel@wur.nl

Web: www.anna.fensel.com