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Scientific machine learning of environmental systems

  • // Denmark
  • University/Institute Name Technical University of Denmark (DTU)
  • University/Institute Name Department of Environmental & Resource Engineering
  • Attendance Type On Campus
  • Position Duration3 years
  • Position Funding Type
  • Application deadlineExpired

Position Details (PhD Program)

The Department of Environmental and Resource Engineering (DTU Sustain) offers a full-time PhD scholarship on scientific machine learning for environmental systems. We are looking for an excellent and highly motivated candidate with an interest in developing the next generation of environmental simulation models. Expected start date is April 1st 2023 or as soon as possible thereafter.

The project aims to develop new environmental simulation models by exploiting recently emerged scientific machine learning techniques. These seek to integrate data-driven machine-learning and theory-driven (numerical) modelling approaches. It is a very rapidly evolving field that holds great potential for creating new models of the environment that are faster and integrate better with observations. In the long run, we expect that impact assessments will be integrated much better across environmental domains, that simulation models will be fast enough to be implemented in web- and mobile environments (and thus become much more accessible to non-experts), and that environmental model results to an increasing degree will be based on observations (sensor data) rather than idealized assumptions.

In this PhD project, you will explore the applicability and limitations of techniques, considering simple conceptual cases as well as real-world cases from a range of environmental domains such as surface water movement, water quality processes or near-surface atmospheric fluxes.

The PhD scholarship is part of DTUs Digitalization initiative. The position will be anchored at DTU Sustains Climate and Monitoring section, which is a lively, interdisciplinary research environment with national and international colleagues from various environmental domains. The section hosts a number of recently started / newly starting PhD students that develop data-driven methods for environmental systems, and that will provide an ideal collaborative environment for the new student. The department has a lively PhD community and puts great emphasis on combining cutting-edge research with a collaborative work and social environment. The research will be in close collaboration with the Scientific Computing section at DTU Compute.

The position is full-time and based at DTU Lyngby Campus, just north of Copenhagen. Copenhagen is renowned around the world for its relaxed atmosphere and high quality of life.

Responsibilities and qualifications
The PhD scholarship will develop new environmental modelling methods that combine traditional numerical approaches, machine learning and data. This includes identifying suitable approaches, transferring them to environmental applications, and benchmarking against alternative methods. Methodological developments will take place in close collaboration with your supervisors and internal and external partners from internationally leading environments and centers of excellence.

The main responsibilities of the student will include data curation and model development in scientific programming languages. In addition, you are expected to disseminate results through scientific publications and conferences, and to contribute to DTUs digitalization efforts, e.g. by supporting the organization of summer schools and participate in relevant teaching activities, including supervision of BSc and MSc students

An ideal candidate will have the following qualifications:

  • A master’s degree in environmental sciences with a strong focus on modelling, or in scientific computing, data science, applied mathematics, or similar
  • Good programming capabilities in scientific languages like Python, Julia or R, and interest in high-performance computing are an advantage
  • Good understanding of environmental processes and related mathematical model formulations (e.g. hydrological cycles)
  • Excellent communication skills, both in writing and oral presentation
  • A willingness and desire to ambitiously engage in interdisciplinary collaboration and work in multinational teams
  • Experience with scientific writing is an advantage

Please note that this is an interdisciplinary project at the interface of environmental engineering, scientific computing and machine learning. It is therefore expected that you will not have the full portfolio of skills at the beginning of the PhD study. During the study you will have the opportunity to extend your skillset through 30 ECTS of coursework from DTUs portfolio as well as universities abroad.

You must have a two-year master’s degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master’s degree.

Approval and Enrolment
The scholarship for the PhD degree is subject to academic approval, and the candidate will be enrolled in one of the general degree programmes at DTU. For information about our enrolment requirements and the general planning of the PhD study programme, please see DTU’s rules for the PhD education.

Interviews will be arranged in the week from Jan 30th to Feb 3rd.

We offer
DTU is a leading technical university globally recognized for the excellence of its research, education, innovation and scientific advice. We offer a rewarding and challenging job in an international environment. We strive for academic excellence in an environment characterized by collegial respect and academic freedom tempered by responsibility.

Salary and appointment terms
The appointment will be based on the collective agreement with the Danish Confederation of Professional Associations. The allowance will be agreed upon with the relevant union. The period of employment is 3 years.

You can read more about career paths at DTU here.

The successful candidate is expected to start on Apr 1st 2023 or as soon as possible thereafter.

Further information
Further information may be obtained from Associate Professor Roland Löwe ([email protected]) from DTU Sustain, and Associate Professor Allan Peter Engsig-Karup ([email protected]) from DTU Compute.

You can read more about DTU Sustain at

If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark. Furthermore, you have the option of joining our monthly free seminar “PhD relocation to Denmark and startup “Zoom” seminar” for all questions regarding the practical matters of moving to Denmark and working as a PhD at DTU.

Application procedure
Your complete online application must be submitted no later than 29 January 2023 (Danish time).

Applications must be submitted as one PDF file containing all materials to be given consideration. To apply, please open the link “Apply now”, fill out the online application form, and attach all your materials in English in one PDF file. The file must include:

  • A letter motivating the application (cover letter)
  • Curriculum vitae
  • Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
  • Names and contact information on 2-3 personal references (we will not contact references without your permission)

You may apply prior to ob­tai­ning your master’s degree but cannot begin before having received it.

Applications received after the deadline will not be considered.

All interested candidates irrespective of age, gender, race, disability, religion or ethnic background are encouraged to apply.

Research Skills Required

Computer/Software Skills Required

Research Areas & Fields of Study involved in the position

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