PhD Position on 3D Modelling of the Subsurface of the Netherlands Using Statistics and Machine Learning (1.0 FTE)

at Utrecht University
Published February 22, 2023
Location Utrecht, Netherlands
Category Machine Learning  
Job Type Scholarship  

Description

Job description Are you interested in statistics, AI, or machine learning and are you eager to apply these methods to solve problems in geology? We welcome you to apply for a position at the Department of Physical Geography at Utrecht University (DPG-UU) in the Netherlands, for a joint project with TNO Geological Survey of the Netherlands.

To support planning of engineering and mining activities on and below the surface, the Geological Survey of the Netherlands (TNO) creates and maintains consistent, nation-wide digital 3D models of the subsurface. Relying on large and diverse geological data sets and advanced geostatistical modelling methodologies, the resulting information contains uncertainties. With new end user requirements and a more diverse, possibly interfering, use of the subsurface data, extending and improving subsurface information is required. Many subsurface-related projects currently encounter bottlenecks regarding the detail, coverage, and quality of subsurface data. For instance, the prediction of geothermal potential, and associated impacts on drinking water supply and seismicity require high resolution subsurface models up to 1200 m containing information on a range of characteristics, such as lithology, facies, flow and thermal properties. In this project you will apply statistics, AI, and/or machine learning methodologies for subsurface modelling to include heterogeneous data streams (borehole data, cone penetration tests, seismic data) sourced from new data collection projects. The volume of data is too large to be interpreted by humans and thus automated methods are required that convert this data to geological information that can be used in models, including measure of uncertainty. Further, a-priori qualitative knowledge, for instance on the spatial distribution of facies, has thus far not been integrated sufficiently in automated spatial modelling methodologies. Approaches are needed to handle this understanding in automated subsurface mapping. In this project you will work in a multi-disciplinary team consisting of geologists, data scientists, and software engineers from both the Department of Physical Geography at Utrecht University and TNO Geological Survey of the Netherlands.

To support academic and personal development, PhD candidates at Utrecht University follow courses and assist in teaching at Bachelor's and Master's level at our faculty. Together these activities amount to approximately 20% of the contracted time. Qualifications We are looking for a colleague who meets the following requirements:

  • You have an MSc degree in data science, statistics, machine learning, AI, or geology/physical geography with expertise in statistics and/or machine learning, or related fields.
  • You want to collaborate with researchers from data science as well as geology/physical geography.
  • You have experience applying statistical or machine learning models in geology or another domain with methods that could be transferred to subsurface characterization.
  • You have a background in geology/physical geography or are keen to acquire knowledge in this domain such that you can apply data science methods for subsurface characterization.
  • You are skilled in communicating your findings through presentations and scientific articles, and with colleagues with different expertise and background. You have good English language skills.
  • You have a team spirit and experience in conducting your work in an independent way.
  • If you don’t meet all the requirements, but you are convinced that you would be a good fit for this position, we warmly invite you to apply.
Offer You will be offered a temporary position (1.0 FTE), initially for one year with an extension to a total of four years upon a successful assessment in the first year, and with the specific intent that it results in a doctorate within this period. The gross salary ranges between €2,541 in the first year and €3,247 in the fourth year of employment (scale P according to the Collective Labour Agreement Dutch Universities) per month for a full-time employment. Salaries are supplemented with a holiday bonus of 8% and a year-end bonus of 8.3% per year.

In addition, Utrecht University offers excellent secondary conditions, including an attractive retirement scheme, (partly paid) parental leave and flexible employment conditions (multiple choice model). For more information, please visit working at Utrecht University. About the organization A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University, the various disciplines collaborate intensively towards major strategic themes. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Sustainability.

Utrecht University's Faculty of Geosciences studies the Earth: from the Earth's core to its surface, including man's spatial and material utilisation of the Earth - always with a focus on sustainability and innovation. With 3,400 students (BSc and MSc) and 720 staff, the Faculty is a strong and challenging organisation. The Faculty of Geosciences is organised in four Departments: Earth Sciences, Human Geography & Spatial Planning, Physical Geography, and Sustainable Development. The faculty is located at Utrecht Science Park near the historical city centre of Utrecht.

The Department of Physical Geography has the ambition to excel in research and education on BSc, MSc and PhD level. Its research focuses on processes, patterns and dynamics of Earth’s continental and coastal systems, and on the interaction between these processes. This knowledge is essential for the sustainable management of our planet and to guarantee the availability of resources for the next generations.

At TNO, we innovate for a healthier, safer and more sustainable life. And for a strong economy. Since 1932, TNO has been developing knowledge and technology for the common good. The Geological Service of the Netherlands - part of TNO - includes geologists, hydrologists, subsurface model developers and IT specialists; a total of more than 250 employees. We all have one thing in common: a fascination for the world beneath our feet and the ambition to understand it in detail. We combine our knowledge with conducting research and providing advice in the fields of sustainable energy, mineral extraction, water management, spatial planning and infrastructure. Work extends from ground level and the seabed to about six kilometers deep. Additional information For more information about this position, please contact Prof. Dr. Derek Karssenberg (Professor in Computational Geography), via d.karssenberg@uu.nl. Apply Everyone deserves to feel at home at our university. We welcome employees with a wide variety of backgrounds and perspectives.

To apply, please send your curriculum vitae, including a letter of motivation via the 'apply' button. Also include the names of at least two referees (with e-mail contact addresses and phone numbers).

The first round of interviews is scheduled for 17 and 18 April 2023.

Note that international candidates needing a visa/work permit for the Netherlands require at least four months processing time after selection and acceptance. This will be arranged with help of the International Service Desk (ISD) of our university. Finding appropriate housing in or near Utrecht is your own responsibility, but the ISD may be able to advise you therewith. For general questions that you might have about working and living in The Netherlands, please consult the Dutch Mobility Portal where much information can be found.

As the PhD candidate will be (partially) present at TNO locations, they require a Certificate of Good Conduct (VOG) from the Ministry of Justice and Security prior to the start of the PhD research. The required statement must be valid during the term of the PhD research and must be renewed during the project. The application deadline is 31/03/2023