Phd position data-driven understanding of world heritage cities

Interested in transforming contaminated plastic waste into upcycled architectural components? Join our research team!

Job description

The cultural significance of UNESCO World Heritage is conventionally only defined by the experts and decision-makers. In the past decade, however, social inclusion and public participation have been growing as goals in heritage management. As proposed by the 2011 UNESCO Recommendation on the Historic Urban Landscape, it is important to document and map the knowledge from a broader public to facilitate more inclusive heritage decision-making processes. People constantly share on social media platforms their perceptions about the cities that they visit or reside, in forms of texts, images, and videos. The ubiquitous geo-located and time-stamped user-generated data and the current advances in data science and AI makes it possible to understand how people perceive the historical urban spaces at large scale, especially those where World Heritage properties are located. This bottom-up knowledge will be informative both for the conservation and management of existing heritage, and for the recognition and nomination of new heritage.

Your interdisciplinary research will study how data science and AI can help understand the perception of world heritage cities by citizens at global level. You will collect and analyse a global dataset of user-generated data (written texts and/or posted images) from social media platforms in cities in part listed as UNESCO World Heritage properties. You will develop analytical frameworks to study both the spatiotemporal patterns (how the data are distributed in space and developed along time) and the semantic contents (what are being discussed) of the dataset. Using the obtained knowledge, you will be able to offer spatial design frameworks and planning suggestions for heritage conservation and urban [re]development.

In the department of Architectural Engineering + Technology we currently have 6 PhD positions open

Job requirements

To be considered for the position, you must have:

• A Master's degree in Urban Data Science, Geographic Information Science, Computational Social Science, Heritage Studies, Geography, Geomatics, Urban Planning, Architecture, or a related discipline.
• A solid experience in the application of data-driven computational research methods informed by social/spatial sciences.
• Programming skills in Python and preferably experience with training and/or applying machine learning models.
• A keen interest in UNESCO World Heritage properties within cities, ranging from the architecture to the urban scale.
• Excellent communication and academic writing skills in English.
• A proactive, curiosity-driven, results-oriented mindset with strong collaborative and creative problem-solving skills to work in an interdisciplinary team.

Additionally, it would be beneficial to have:

• Research experience in text mining and/or multimodal machine learning, preferably contributing to academic publications.
• A mindset that is culturally oriented, passionate about diversity and inclusivity, and/or familiar with different cultures and world regions.

TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.
At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.
Challenge. Change. Impact!

Faculty Architecture and the Built Environment
The Faculty of Architecture and the Built Environment has a leading role in education and research worldwide. The driving force behind the faculty's success is its robust research profile combined with the energy and creativity of its student body and academic community. It is buzzing with energy from early in the morning until late at night, with four thousand people studying, working, designing, conducting research and acquiring and disseminating knowledge. Our faculty has a strong focus on 'design-oriented research', which has given it a top position in world rankings.

Staff and students are working to improve the built environment with the help of a broad set of disciplines, including architectural design, urban planning, building technology, social sciences, process management, and geo-information science. The faculty works closely with other faculties, universities, private parties, and the public sector, and has an extensive network in the Netherlands as well as internationally.
here to go to the website of the Faculty of Architecture and the Built Environment.

Are you interested in this vacancy? Please apply no later than 2 February 2025 (local Dutch time: UTC time + 2 hrs) via the application button and upload the following documents:

• Detailed CV - highlight examples of projects and/or achievements that demonstrate skills relevant to the advertised position.
• Motivation letter (no more than 600 words) addressing your interests and describing how your experience and plans fit with the position.
• MSc thesis (if finished) and, if applicable, one or two notable conference/journal publications you have co-authored.
• Undergraduate and graduate transcripts (if finished).

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis. For more details please check the .

Please note:

• You can apply online. We will not process applications sent by email and/or post.
• A pre-employment screening can be part of the selection procedure.
• National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
• Please do not contact us for unsolicited services.