Challenge: Confident and robust decision-making under uncertainty
Change: Leverage combinatorial and algorithmic methods for sensitivity analysis
Impact: Enable confident and robust decision-making
Modern decision-making increasingly relies on algorithms that provide recommendations based on models of the real-world problem. These models take many parameters as input. Wouldn't it be great if we knew *which input parameters* in such model *really matter* for its outcomes?
Knowing which parameters are really important helps decision-makers to allocate resources towards obtaining more accurate estimates of those parameters, to draft contingency plans, and to provide guarantees on the robustness of their decisions w.r.t. Specific input parameters.
Classical approaches to this sensitivity analysis are based on simulations. These are computationally expensive an might miss important variables.
In this project we will explore logic-based methods that identify critical/important parameters based on the *structure* of the problem, instead. This allows us to provide *formal guarantees* on the correctness of our results, enabling confident decision-making by end-users. We will explore how the structure of logic problems can inform statistical testing methods. Leveraging structural knowledge can help limit the number of required tests to identify, for example, faulty components in a power network, leading to stronger guarantees with less data.
The supervisory team for this project consists of dr. Ir. Sicco Verwer (promotor), dr. Fabian Mies and dr. Anna Latour (co-promotores).
Job description
In your research you will build on and expand your knowledge of modelling- and solving paradigms like Boolean Satisfiability, Constraint Programming, Mixed-Integer (Linear) Programming. Additionally you will work on methods for reasoning about discrete probability distributions, sampling from complex spaces, and statistical analysis methods.
While doing so, you will collaborate with other researchers and software engineers to build usable tools for both the scientific community and societal stakeholders. You will communicate your research findings by publishing in and presenting at top-tier academic conferences and journals. This provides excellent opportunities for building an international network of experienced researchers and experts.
Work environment
You will work in the Algorithmics section at the Software Technology (ST) department and collaborate with the Statistic section of the Delft Institute of Applied Mathematics (DIAM). In the Algorithmics section you will become part of a dynamic and diverse environment of PhD and postdoc researchers excited about making theoretical and algorithmic contributions in intelligent decision making. We aim to deal with the scalability challenge inherent in many such applications, to understand how to learn models that are useful for upstream planning, scheduling, and verification tasks, and how to deal with their uncertainty. Further, we aim to understand how to effectively incorporate behaviour and preferences of stakeholders into the algorithmic decision-making process.
TU Delft hosts a vibrant interdisciplinary community, facilitated through cross-faculty institutes and seminar series addressing a range of societal problems, including climate change, the energy transition, and artificial intelligence. As a PhD candidate, you will collaborate with experienced researchers, attend conferences, and experience an international research environment. The position will focus on research, with optional contributions to education and supervision of bachelor and master students.
Why join us?
- Innovative research: Work on cutting-edge modelling and solving techniques that address decision-making challenges.
- Collaborative environment: Engage with multiple work packages and different experts in the field.
- Impactful work: Apply your results to pressing challenges in engineering and policy making.
If you are a computer science enthusiast with an interest in optimisation and decision-making, we invite you to apply and be part of this transformative
Job requirements
Required (by the Graduate School of TU Delft):
- Master's degree in Computer Science, Operations Research, or a related field.
- Proficiency in the English language (https://www.tudelft.nl/onderwijs/opleidingen/phd/admission)
Optional requirements:
- Demonstrable knowledge of reasoning paradigms like Boolean Satisfiability, Constraint Programming or Mixed Integer (Linear) Programming.
- Programming skills in languages such as Java, Python or C++.
- Solid understanding of statistics and probability theory, in particular hypothesis testing.
- Excellent critical and analytical thinking skills.
- A proven record and interest in further developing your research skills, such as a critical attitude, self-organisation and academic writing.
- A strong affinity with and enthusiasm for state-of-the-art, algorithmic and optimisation techniques, and in applying these to support decision-making.
- An affinity with teaching and guiding students.
- The ability to work in a team and take initiative.
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 Electrical Engineering, Mathematics and Computer Science
The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment - which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.
to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.