Postdoc Robust Thermodynamics for CO2 and H2 Reservoir Mixtures

Job description

Phase behavior plays an important role in subsurface flow and transport of large-scale CO2 sequestration operations. This project is dedicated to the development of robust and efficient algorithms for predicting of phase behavior and properties for mixtures including brine and composition of gasses relevant to CO2 and H2 injection in the subsurface reservoirs. All algorithms will be designed for performing at both CPU and GPU architectures based on the modern Equations of State. The resulting library will be tested for reservoir simulation of synthetic and real CO2 and H2 injection projects.

Job requirements
We welcome applicants from various engineering disciplines, including (but not limited to) Civil, Mechanical and Petroleum Engineering. Our strict requirement is that the candidates must have strong scientific skills on computational methods, numerical analyses, and programming (C++ and Python). Strong experience with darts-flash is expected. Candidates with good background on thermodynamics and optimization methods will be preferred.

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 of Civil Engineering and Geosciences
The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Click here to go to the website of the Faculty of Civil Engineering & Geosciences.

Postdoc Robust Thermodynamics for CO2 and H2 Reservoir Mixtures

Job description

Phase behavior plays an important role in subsurface flow and transport of large-scale CO2 sequestration operations. This project is dedicated to the development of robust and efficient algorithms for predicting of phase behavior and properties for mixtures including brine and composition of gasses relevant to CO2 and H2 injection in the subsurface reservoirs. All algorithms will be designed for performing at both CPU and GPU architectures based on the modern Equations of State. The resulting library will be tested for reservoir simulation of synthetic and real CO2 and H2 injection projects.

Job requirements
We welcome applicants from various engineering disciplines, including (but not limited to) Civil, Mechanical and Petroleum Engineering. Our strict requirement is that the candidates must have strong scientific skills on computational methods, numerical analyses, and programming (C++ and Python). Strong experience with darts-flash is expected. Candidates with good background on thermodynamics and optimization methods will be preferred.

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 of Civil Engineering and Geosciences
The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource availability, urbanisation and clean water. Our research projects are conducted in close cooperation with a wide range of research institutions. CEG is convinced of the importance of open science and supports its scientists in integrating open science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.

Click here to go to the website of the Faculty of Civil Engineering & Geosciences.

PhD Position Symbolic AI and Reasoning Under Uncertainty

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.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

PhD Position Symbolic AI and Reasoning Under Uncertainty

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.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

PhD Position Data-Driven Health Monitoring of Floating Wind Turbines

Job description
We are seeking a motivated researcher to join our team in advancing innovative approaches for mitigating wake interaction effects in floating wind turbines. Recent advancements in dynamic actuation strategies have shown promise for enhancing wake mixing, but significant gaps remain in understanding the complex behavior and nonlinearities of mooring systems. This project aims to address these gaps by developing hardware-in-the-loop facilities for emulating mooring line nonlinearities at model scale and devising active control and health monitoring strategies. These efforts are aligned with the HybridLabs project, which leverages bio-inspired, data-driven control techniques in controlled wind tunnel environments.

The successful candidate will focus on real-time data-driven control and health monitoring techniques for mooring systems and floating wind turbines. Key responsibilities include designing an experimental setup at TU Delft to mimic the realistic nonlinearities of mooring lines, implementing and testing control algorithms, and conducting a comprehensive test campaign using state-of-the-art facilities. This position offers a unique opportunity to contribute to groundbreaking research at the intersection of renewable energy, control systems, and experimental mechanics.

Job requirements
The successful candidate has the following qualifications:

• A M.Sc. degree in systems and control, wind energy or hydrodynamics.
• Fundamental knowledge in the field of optimization and control.
• The capacity to communicate effectively with peers, students and stakeholders in the application field.
• Good programming skills are a plus: MATLAB, Python, Git.
• Fluency in English.
• An open personality and good communication skills in written and spoken English.

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 Mechanical Engineering
From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our environment and discover its underlying mechanisms, research and education at the ME faculty focusses on fundamental understanding, design, production including application and product improvement, materials, processes and (mechanical) systems.

ME is a dynamic and innovative faculty with high-tech lab facilities and international reach. It’s a large faculty but also versatile, so we can often make unique connections by combining different disciplines. This is reflected in ME’s outstanding, state-of-the-art education, which trains students to become responsible and socially engaged engineers and scientists. We translate our knowledge and insights into solutions to societal issues, contributing to a sustainable society and to the development of prosperity and well-being. That is what unites us in pioneering research, inspiring education and (inter)national cooperation.

Click here to go to the website of the Faculty of Mechanical Engineering. Do you want to experience working at our faculty? These videos will introduce you to some of our researchers and their work.