The TU Delft Artificial Intelligence (AI) Lab for Design, Analysis, and Optimization in Architecture & the Built Environment (AiDAPT) invites applications for one PhD position in the area of AI-driven decision-support analytics for stochastic life-cycle assessment & optimization of structural systems and infrastructure under uncertainties.
We are looking for candidates highly motivated to work at the confluence of structural engineering, systems risk & reliability, optimization, and AI, towards addressing safety and resilience challenges of an aging, growing, and changing built environment. Recent advances in AI provide us with unprecedented capabilities to scale up and automate our design, information processing, and structural intervention strategies in complex and high-dimensional engineering settings. In this direction, of particular interest to this research is how we can harness and shape AI to make optimal and dynamic decisions in the presence of multiple stressors and hazards; uncertainties in structural health data and models; evolving environmental and anthropogenic demands; resource limitations; and long-term socioeconomic risks.
The research stream delineated by the position is aimed at providing novel insights in the ways the built environment can optimally adapt and change in the years to come, supported by innovative synergies between data-driven intelligence and model-based engineering. In this direction, this research is expected to produce new knowledge that integrates deep learning, reinforcement learning and statistical inference techniques with optimal decision theory, structural health monitoring, and structural mechanics methodologies.
The successful candidate will join the research group of Dr. Charalampos Andriotis, at the Chair of Structural Design & Mechanics (SD+M), in the Faculty of Architecture and the Built Environment (ABE). The position is funded for a duration of 5 years, during which the appointed candidate will (i) undertake research on her/his PhD topics and (ii) assist with the educational and research agenda of AiDAPT and the host Chair.
- MSc in Civil or Architectural Engineering (preferred), Industrial or Electrical Engineering, Computer Science, and related fields;
- Strong background in at least two of structural mechanics/dynamics, risk & reliability, uncertainty quantification, machine learning, and optimization;
- Working knowledge or expertise on data-driven and machine learning methods, and interest to apply this knowledge in structural systems and infrastructure of the built environment;
- Excellent programming skills (Matlab, Python, C++, or similar);
- Proficient use of English (oral and written).
- Teaching interest and/or experience in AI- and SD+M-related courses.
- Ability to work in a team, take initiatives, and be results-oriented.
Conditions of employment
TU Delft offers DAI-Lab PhD candidates a 5-year contract, including an official progress evaluation after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2325 per month in the first year to € 3217 in the fifth year. As a PhD candidate, you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff, and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related research skills. TU Delft offers a customizable compensation package, discounts on health insurance and sport memberships, and a monthly work cost contribution. For international applicants, we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
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. For generations, our engineers have proven to be entrepreneurial problem-solvers both in business and in a social context. TU Delft offers 16 Bachelor’s and 32 Master’s programmes to more than 23,000 students. Our scientific staff consists of 3,500 staff members and 2,800 PhD candidates. Together we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
AiDAPT is TU Delft’s AI-Lab for Design, Analysis and Optimization in the Faculty of Architecture & the Built Environment, directed by Dr. Charalampos Andriotis and Dr. Seyran Khademi. At AiDAPT, we harness and shape AI to support long-term, adaptive, and evidence-based abstraction and synthesis of structural and architectural choices, towards a more sustainable and resilient built environment. The host Chair of the PhD position is SD+M. SD+M contributes to research and education related to structural analysis and design in ABE and other Faculties within TU Delft, such as CEG and 3mE. With the newly established AiDAPT Lab, SD+M is further expanding its bridges with ECEE, and With-AI and In-AI Faculties of other AI-Labs. Led by Prof. Mauro Overend, SD+M is a dynamic group of researchers and educators exploring ways of transforming structures into the safe, sustainable, and elegant built systems of the future through leading-edge research and inspirational education.
The position will remain open until December 31st, 2021 (local Dutch time: UTC time + 2 hrs). Applicants are encouraged to apply online before November 15th, when screening of applications will begin.
You must apply via the ‘Apply now’ button. Application via email will not be processed.
For additional information about the position please contact Dr. Charalampos Andriotis at firstname.lastname@example.org.
For information about the selection procedure, please contact Caro Coemans, HR advisor, email: email@example.com.
To apply submit 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 fits with the position;
- Contact information for two references (letters not required at this stage);
- MSc thesis and, if applicable, one or two notable publications you have authored;
- Undergraduate and graduate transcripts.