代尔夫特理工大学

High-resolution subsurface characterization using seismic inversion-based imaging methods combined with geologic prior knowledge/machine learning

项目介绍

A geo-imaging challenge: Combine deterministic seismic inversion, machine learning and geologic prior knowledge to arrive at beyond-wavelength resolution of fine-scaled subsurface structures

Job description

The seismic method has been used for several application fields of subsurface exploration and monitoring. The resolution of the final subsurface information is traditionally limited by the local wavelength in the medium. In addition, traditional target area inversion for the elastic parameters is based on local 1.5D assumptions of the layering. In many cases the subsurface structures have a multi-dimensional character with complex depositional structures. But in case prior knowledge is available about possible fine-scaled local stratigraphic architectures of the subsurface structures and using Machine Learning to link this information to the observed seismic data signatures, we aim at inverting seismic data beyond traditional resolution.

This proposed PhD project is a duo-project with a geologic counterpart, in which all relevant geologic scenario information is generated. Thus, the proposed project has a strong emphasis on wave theory, seismic imaging and inversion and Machine Learning. It is within the context of a large industry-sponsored geo-imaging project Delphi (that is mostly executed within Delft University of Technology. 

Department
Research in the department of Imaging Physics is aimed at developing novel instrumentation and methodology in imaging science and sensing technology. Our research products extend existing boundaries in terms of spatial resolution, temporal resolution and information/data throughput. We are pioneers in developing advanced concepts of computational imaging, a marriage between cleverly designed imaging systems and sophisticated post-processing. In everything we do, there is a core of cutting edge physics and engineering of high-tech instruments, of the use of the most advanced computing techniques, and of a very close link to real-life applications. Our work has clear societal impact in the areas of life sciences, healthcare, and industry.

Requirements

  • Having a university M.Sc-level background in the field of Applied Physics, Applied Mathematics, Electrical Engineering or Geophysics
  • Being an independent researcher with implementation skills in Python (preferred), Matlab, C or other computer languages.
  • Having experience with research and development in the field of signal processing, wave theory, inverse problems, geophysical data analysis and machine learning.
  • Being able to communicate and cooperate with other researchers in a large and multi-disciplinary research project.
  • Being able to write scientific publications and present results at international audiences.
  • Being a creative researcher with innovative ideas that is eager to learn possible missing parts of scientific background and skills

Conditions of employment

TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 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 sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.

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 and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.

Challenge. Change. Impact! 

Faculty Applied Sciences

With more than 1,000 employees, including 135 pioneering principal investigators, as well as a population of about 3,400 passionate students, the Faculty of Applied Sciences is an inspiring scientific ecosystem. Focusing on key enabling technologies, such as quantum- and nanotechnology, photonics, biotechnology, synthetic biology and materials for energy storage and conversion, our faculty aims to provide solutions to important problems of the 21st century. To that end, we train students in broad Bachelor’s and specialist Master’s programmes with a strong research component. Our scientists conduct ground-breaking fundamental and applied research in the fields of Life and Health Science & Technology, Nanoscience, Chemical Engineering, Radiation Science & Technology, and Engineering Physics. We are also training the next generation of high school teachers and science communicators.

Click here to go to the website of the Faculty of Applied Sciences.

Additional information

For more information about this vacancy, please contact Dr. D.J. Verschuur.    

Application procedure

Are you interested in this vacancy? Please apply before [15 September 2021] via the application button and upload your 1-page Motivation letter, your CV, undergraduate and graduate transcripts; a (part of your) M.Sc. thesis or a paper that you have written, in which you demonstrate your writing skills.

录取要求

  • Having a university M.Sc-level background in the field of Applied Physics, Applied Mathematics, Electrical Engineering or Geophysics
  • Being an independent researcher with implementation skills in Python (preferred), Matlab, C or other computer languages.
  • Having experience with research and development in the field of signal processing, wave theory, inverse problems, geophysical data analysis and machine learning.
  • Being able to communicate and cooperate with other researchers in a large and multi-disciplinary research project.
  • Being able to write scientific publications and present results at international audiences.
  • Being a creative researcher with innovative ideas that is eager to learn possible missing parts of scientific background and skills

项目概览

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截止日期 2021-09-15
代尔夫特理工大学

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代尔夫特理工大学是荷兰历史最悠久、规模最大、综合实力最强的理工大学,系欧洲顶尖工科联盟IDEA联盟成员。
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联系方式

电话: +31 (0)15 27 89111

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