Vacancy: PhD researchers in urban data science

Positions and research agenda

The Urban Analytics Lab, a research group at the National University of Singapore (NUS), is seeking two PhD researchers in urban data science. These are fully funded PhD positions for four years during which the successful candidates are expected to fulfil the requirements for a PhD degree at NUS.

The PhD researchers will develop their research line and grow into independent scholars.

They will also contribute to teaching activities and various service tasks in the research group and department such as co-supervision of master students, assisting with the preparation of proposals, and managing resources and visits.

There are two PhD positions available, one in each of the following broad areas, within which the candidate will develop their own focused PhD project:

1. Sensing urban changes and dynamics with emerging urban data (PhD-1). Cities change daily and continuously. The established instruments for observing change, predominantly remote sensing, view cities from above and at intervals, but much urban change is subtle and invisible from a top-down view, happens between acquisitions, or leaves no substantial physical trace. This PhD will develop new urban representations, methods and instruments for urban change detection, capturing the dynamics that conventional techniques miss, from time-series street-level imagery to continuous crowdsourced data streams such as place reviews. Building on the detected changes, the project may also study their causes and effects, e.g. drivers such as climate and economic conditions, what they lead to in turn, or whether planning interventions actually work, with the exact focus shaped by the candidate’s interests. This position suits applicants with strong foundations in computer science, geoinformatics and/or urban planning, some background in statistics, and curiosity about how cities change and adapt.

2. Trustworthy Urban AI: quality, bias and uncertainty (PhD-2). AI is being deployed rapidly everywhere, but can we trust the data and models that underpin urban analytics? Cities are increasingly measured, modelled and managed by AI built on multimodal urban data (e.g. imagery, text, sensor streams), much of it of unknown quality and, in the generative-AI era, of potentially eroding reliability and authenticity. This PhD will advance the science of reliability for Urban AI. Examples include developing methods to estimate the completeness and bias of urban datasets without ground truth; tracing how uncertainty propagates from urban data through models to indicators and decisions, and how it varies across space; and benchmarking Urban AI systems – including geospatial foundation models – for robustness to data contamination, hallucination, and poor transferability across cities. The project may also go beyond diagnosis, for instance by examining whether AI agents can monitor and improve the quality of urban data. This position suits applicants with strong quantitative, statistical or machine learning foundations.

The topics above are starting points and broader frames. The researchers will be expected to develop their focused line of research based on discussions with the advisor and other members of the research group during the first stage of their PhD.

The PhD students will be enrolled in the PhD programme of our Department of Architecture at the College of Design and Engineering. They will be supervised by the Principal Investigator of the Lab – Prof Filip Biljecki, and will collaborate with other members of the research group.

Candidates should have strong computational and research skills and a master’s degree in computer science, geographical information science, urban planning, geomatics, engineering, statistics, or another relevant field of study, with evidence of research aptitude.

The Lab and Department provide a motivating, conducive, and flexible environment that enables researchers to explore their interests and curiosity, and build skills required for future career steps. Our current and former members, including PhD graduates, have published dozens of impactful papers in leading journals and have secured meaningful and significant placements in the continuation of their academic career, including faculty positions. Their outputs and accomplishments transcend papers, and also include invited talks, community initiatives, and open datasets and open-source software.

Required qualifications

A strong interest in urban analytics / GIScience / GeoAI, supported by relevant technical and scientific skills, together with proactivity, initiative, ownership, and continuous learning aspirations, is key to these positions. Please also check this guide that we prepared (including our expectations from a PhD).

You should demonstrate that you possess:

• A master’s degree 🎓 in a related discipline from a reputable university. Current MSc candidates are eligible to apply as well, provided that they are in the final stage of their studies and that their degree will be conferred before the start of the PhD programme.
• Evidence of research aptitude, such as a publication, research internship / experience, and/or a compelling proposal.
• Ability to identify research gaps and conceptualise research plans and methods to address them.
• Proficiency in one or more of the following areas: urban data science, computer science, GIScience, geomatics, remote sensing (in the urban/built environment), computer vision / deep learning, urban planning, and/or urban simulations. We do not expect applicants to be proficient in all the topics we work on 🦄, however, we ask them to demonstrate that they have skills in at least one of the related topics, have affinity for expanding their expertise beyond their main focus, and have solid ideas about how to continue their research aspirations.
• Very good communication skills in English (oral and written).
• Strong computational skills and experience with programming and data science toolkits. We will prioritise applicants who can demonstrate these qualities through a GitHub profile or similar evidence. Further, proficiency with (i) general academic tools such as LaTeX; (ii) geospatial tools such as QGIS; (iii) plotting libraries such as ggplot or matplotlib; and (iv) statistics is a strong plus.
• An ability to work with others and in an international environment.
• Curiosity and passion to explore new concepts, methods and technologies, and capability of identifying and quickly learning the most suitable tools for the research on the go.
• Optional: a positive and proactive stance on open science, preferably with demonstrated activities such as using and developing open-source software, releasing data as open data, and promoting reproducible research.

Our offer

• You will be working on compelling research activities at the forefront of urban informatics and associated disciplines in a unique research group that is gaining strong momentum in Singapore and globally, and be a member of a vibrant community at a leading research university. Further, we collaborate with other research groups at NUS and beyond, which often leads to multidisciplinary efforts, exposing you to new topics and experts.
• You will advance your research and transferable skills required for the next stage of your career. You will be welcome to explore and learn new tools and technologies, expand your current skillset, and gain potentially new experience such as funding applications and management that may be critical for your next career step (e.g. faculty position).
• You will be involved in steering the direction of our research group, participate in discussions continuously revisiting and enhancing our research agenda, and take a leadership role in one of the managerial tasks.
• You will work in a research and educational environment where you may not only contribute to your own development, but also to others, e.g. by supervising master’s theses that may arise as part of the research.
• Opportunity to make impactful contributions in the field, on globally relevant and growing topics.
• Visibility and exposure of your work.
• Expansion of your network through potential contact with academic, industrial, and governmental partners, both locally and internationally.
• A diverse, inclusive, friendly, and flexible working environment.
• Flexibility to explore new ideas and an opportunity to experiment with the state of the art.

A PhD at the NUS College of Design and Engineering and Department of Architecture

The PhD researchers will be enrolled in the graduate programme of our Department and our College, and will be expected to fulfil requirements such as coursework and Qualifying Examination. For more information, check this page. Please also check this guide that we prepared (including a FAQ).

PhD scholarship

The PhD positions are fully funded through the NUS Research Scholarship (i.e. tuition fees covered, plus a stipend for living expenses). The terms of this scholarship are set by NUS. Please read more here.

There is no bond.

Duration and location

Each position is funded for four years. The positions have two possible start dates: August 2027 and January 2028 (in alignment with the start of the semesters at NUS).

The PhD is based in Singapore. This is not a remote position.

The PhD student will work in our research group. We offer flexible working arrangements similar to most academic environments (e.g. no strict office hours and the possibility to spend a portion of time working from home).

Context

National University of Singapore

The National University of Singapore (NUS) is ranked consistently as one of the world’s top universities. NUS offers a global approach to education and research with a focus on Asian perspectives and expertise. It was founded in 1905 and is today Singapore’s flagship university. It aspires to be a vital community of academics, researchers, staff, students and alumni working together in a spirit of innovation and enterprise for a better world.

Singapore

Singapore is a tropical and cosmopolitan English-speaking island city-state located in Southeast Asia near the equator. Thanks to a unique combination of factors such as culture, languages, business environment and governance, it is a distinct and enjoyable place to live and work, and positioned to act as a bridge between the East and the West. Singapore tops many international rankings in education, quality of life, infrastructure, housing, and healthcare. For example, it is considered to be the #1 most competitive country and ranks 1st worldwide on perceived safety, successfully attracting talents from all parts of the globe by offering first-class living and working experience in the heart of Southeast Asia, and a very clean and efficient environment.

And of course, it has great food and weather, with many popular tourist destinations in the region just a short flight away. ☀️ 🍜 ✈️

Urban Analytics Lab

The NUS Urban Analytics Lab is a multidisciplinary research group established in 2019 focusing on urban informatics at the NUS College of Design and Engineering. Overall, being part of our Lab presents a rare and holistic opportunity in Singapore and this part of Asia to be involved in the entire urban informatics and geospatial ecosystem under the same roof: from investigating new means to urban sensing all the way to developing applications and tools, while continuously exploring new frontiers in the field such as the interface with AI and contributions to domains such as urban planning, mobility, energy, and climate to make cities smarter and more data-driven.

Our work is consistently published in leading international journals.

Our Lab is located at SDE4, the first newly-built net-zero energy building in Singapore, and the first university building in the world to be WELL Certified Gold.

Our department is consistently ranked among the best in the world.

The PhD supervisor and principal investigator of the Lab was awarded the prestigious Presidential Young Professorship in 2020, and was granted tenure in 2026, affirming the relevance of the research agenda and its impact, and supporting the long-term development of the research group.

Feel free to check the rest of our website for further detailed information (e.g. our About page) and watch the video below.

Application

Before preparing your application, please make sure that you understand:

• What we do.
• How we do it.
• What a PhD at NUS looks like and what we expect: please read our guide for prospective applicants (incl. a FAQ) to learn more about it and also visit the NUS/CDE website for the PhD programme.

Please apply by email (write “Application: PhD-1” in the subject for the first position, or “Application: PhD-2” for the second one), including the following:

• Academic CV
• Which intake you prefer (August 2027 or January 2028)
• A cover letter / statement (about one page) briefly indicating:
  • (i) your computational skills and relevant experience so far and how they would translate to the benefit of this PhD position, and your learning goals and aspirations;
  • (ii) outlook on one of the aforementioned topics with some ideas and how you plan to tackle such a problem;
  • (iii) how you intend to contribute to our growing research group and enhance its activities.
  • Keep it short and simple, please. A few paragraphs for each of these points is sufficient.
• A PhD research proposal addressing either of the two topics (up to a few pages).
• Links to relevant materials such as a paper published in a reputable conference or journal that evidences your research aptitude, background and experience. Please do not provide group projects from your coursework or similar. Only material relevant to this position will be considered.
• Names and contact information for three referees. There is no need to submit recommendation letters at this stage. By providing this information, we assume that we have your and their permission to contact them to learn more about you. Letters will be required later from applicants selected for the positions.
• Other materials showing that you meet the required qualifications and aptitude for research, e.g. link to a public GitHub repository you have developed, recorded presentation, and portfolio. Candidates who can demonstrate strong computational skills and have research experience will be prioritised.

We appreciate your understanding that only applicants shortlisted for the interview will be notified. The selected candidates will later be asked to provide the full documentation, e.g. academic certificates and transcripts, copy of ID, and three letters of recommendation; and go through the application to the PhD programme at NUS for official admission.

Contact

For more information feel free to contact Prof Filip Biljecki.