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Job advertisement PhD Position for Adaptive Nonlinear Data Assimilation in Subsurface Systems

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PhD Position for Adaptive Nonlinear Data Assimilation in Subsurface Systems

Position
PhD Position for Adaptive Nonlinear Data Assimilation in Subsurface Systems

Employer
Delft University of Technology logo

Delft University of Technology

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 Civil Engineering & 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.

Homepage: https://www.tudelft.nl/


Location
Delft, Netherlands

Sector
Academic

Relevant divisions
Energy, Resources and the Environment (ERE)
Hydrological Sciences (HS)
Nonlinear Processes in Geosciences (NP)

Type
Full time

Level
Entry level

Salary
Open

Required education
Master

Application deadline
Open until the position is filled

Posted
11 July 2024

Job description

Challenge: Advancing the energy transition requires understanding complex subsurface environments.

Change: Developing an innovative nonlinear data assimilation strategy that can adapt itself to the challenges of different natural systems.

Impact: This method will permit safer, more predictable operations in the subsurface and beyond.

Job description

The subsurface plays a critical role in tackling the challenges of a changing climate. It provides drinking water amidst increasingly frequent droughts, and it is a keystone of the energy transition by providing geothermal energy and storage space for hydrogen. Despite its importance, our insights into the subsurface’s properties and processes are scarce, limiting our ability to fully characterize this environment. The resulting uncertainties require careful analysis to inform societally responsible subsurface operations: How can we sustainably heat as many homes as possible? Where shall we establish the next hydrogen storage reservoir? What can we do to mitigate our operation’s environmental and economic risks?

To answer such questions, data assimilation systematically combines numerical models with data to explore different possibilities of what the true system could be like, but its implementation remains a challenge in complex systems. Most data assimilation methods either over-simplify or are prohibitively inefficient, which compromises our decision-making. In this project, you will join a collaboration between TU Delft and the Norwegian energy company Equinor to co-develop an improved data assimilation strategy that uses a statistical method related to normalizing flows and diffusion models. This method can exploit advanced information about the numerical model, such as which variables are indirectly related to each other (conditional independence) or degrees of nonlinearity (How complex do we have to make our updates?). This allows us to create a powerful data assimilation framework that is always as simple as possible and as complex as necessary, which yields improved subsurface characterizations that will enable better, more reliable decision making.

As a PhD student at TU Delft, you will:

  • Familiarize yourself with the methodological foundations of triangular measure transport and data assimilation
  • Co-develop a scalable, adaptive, nonlinear data assimilation method based on triangular transport
  • Explore innovative strategies to adapt the method to different environmental systems
  • Apply the resulting algorithm to analyse the properties and uncertainties of a real geothermal operation

This four-year project is part of a collaboration between TU Delft and DA research at Equinor in Bergen, Norway. You will join the reservoir engineering section at TU Delft’s Department of Geoscience & Engineering, where you will find a vibrant and collaborative environment in which you will have the opportunity to interact with experts in data assimilation, geothermal energy, and numerical simulation. You will be encouraged to learn new skills and develop your own ideas, and you will share your findings at conferences and in peer-reviewed journals. These experiences will pave the way for diverse career paths in industry, consultancy, governmental agencies, or academia.

Requirements

  • You hold a Masters degree in geoscience, geophysics, applied mathematics/statistics, or a similar field
  • You thrive on systematic, code-based research, and have an aptitude for abstract or mathematical thinking.
  • You have a keen interest in data assimilation and machine learning, and are excited to explore their applications in complex environmental systems
  • You have experience with Python or a similar programming language. Experience with computationally intensive numerical methods is a plus.
  • You are a highly motivated and self-driven researcher, capable of working both independently and as part of a team
  • You have an excellent command of written and spoken English

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 Graduate Schools Admission Requirements.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth 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 and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.

Additional information

For more information about this vacancy, please contact Dr. Max Ramgraber (m.ramgraber@tudelft.nl).


How to apply

Application procedure

Are you interested in this vacancy? Please apply no later than 11 August 2024 via this link and upload:

  • A motivation letter (max. 800 words) outlining your interest in pursuing a PhD and your interest for this particular project.
  • A curriculum vitae including, if available, a link to your MSc thesis.
  • Academic transcript, including grades for your qualifying degrees (BSc, MSc)
  • Contact information for two referees we can call or email for feedback (no letters are needed at this stage).

After an initial selection, we plan to have a first round of online interviews in the week of 19.08.2024, and a second round the week after. We understand that you might have other commitments during the summer and will do our best to be flexible when setting up the interviews.

We are acutely aware that we are a diverse society and not every talented student will have had the same opportunities to advance their careers. We therefore pledge to fully account for any particular circumstances that the applicants disclose (e.g. parental leave, caring duties, part-time jobs to support studies, disabilities etc.) to ensure an inclusive and fair recruitment process that does not rely purely on common research metrics. Our goal is to help the next generation of scientists thrive in a safe and inclusive environment.

We are looking forward to receiving your application!

Max Ramgraber (TU Delft), Berent Lunde (Equinor), Femke Vossepoel (TU Delft)

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.
  • Please do not contact us for unsolicited services.