PhD on machine learning-based flood forecasting at national scale

Organisation/Company

Geological Survey of Denmark and Greenland (GEUS)

Research Field

Geosciences » Hydrology
Engineering » Computer engineering
Environmental science » Water science

Researcher Profile

First Stage Researcher (R1)

Country

Denmark

Application Deadline

9 Oct 2023 - 11:59 (Europe/Copenhagen)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

37

Offer Starting Date

1 Nov 2023

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

Yes

With this PhD position, you have the opportunity to develop cutting-edge modelling systems to provide key hydrological information to the Danish society. The real-time forecasting system to be developed will leverage information on flood inundation risk to increase resilience towards hydrological extremes.

The PhD project is part of a large project that involves collaboration with the Danish Meteorological Institute (DMI), the Danish Agency for Data Supply and Infrastructure (SDFI) and the Danish Environmental Protection Agency (MST).

Job description
Within the PhD project you will conduct cutting-edge research within large-scale flood inundation modelling utilizing a suite of modelling tools, i.e., hydrological models, hydrodynamic models, machine learning (ML) and hybrid models. The latter benefit from combining the best of the alternative modelling approaches. You will work with satellite-derived (e.g. Sentinel SAR and optical data) inundation maps, observed water levels in streams, precipitation data, and high-resolution digital elevation models to further develop and contrast the alternative modelling approaches. Your project will be transdisciplinary spanning over hydrology, remote sensing and ML, in particular spatial Deep Learning approaches.      

The specific objectives include (1) the development of a novel ML-based flood inundation modelling framework, (2) the inter-comparison of alternative methods (ML-stand alone, hydrodynamic models and different degrees of novel hybrid models) to model inundated areas, (3) transferring the methods from Denmark to different geographic settings.

As a PhD at GEUS, you will contribute to the further development of the ongoing efforts to operationalize the national coupled groundwater surface water model (DK-Model) to provide real-time and forecast information on the status of groundwater and surface water to the Danish society. You will work closely with a Post Doc who will be hired on the same project starting in January 2024. You will be enrolled at the PhD school at the Faculty of SCIENCE at the University of Copenhagen. At the Department of Geosciences and Natural Resource Management at University of Copenhagen, you will also interact and collaborate with early career researchers from related projects, e.g., the recently launched Global Wetland Center .      

You should expect to broaden your existing field by covering elements of hydrological modelling, remote sensing, machine learning, data analysis and data management. Your research findings should be published in leading journals within the field. You are expected to contribute to the internationalization of the project by attending international conferences and going on an external research stay during the course of your PhD project.       

Research Field

Geosciences » Hydrology

Education Level

Master Degree or equivalent

Research Field

Environmental science

Education Level

Master Degree or equivalent

You are expected to hold an academic university degree (MSc in geosciences, environmental sciences or engineering, physics, computer science or related) and the appointment will be made based on your study record and related work experience. Special emphasis will be placed on experience with numerical hydrological/hydrodynamic modelling and machine learning. In addition, specific knowledge or experience with satellite remote sensing, geographical information systems (GIS) and programming skills (ideally python) will be an asset. Moreover, previous involvement in dissemination of scientific results via peer-reviewed journals or conferences will be positively evaluated.

Special consideration will be given to the candidate’s ability to embrace a broad range of activities and collaborate within a team of colleagues on a daily basis. The candidate must also master English and if they do not speak Danish, they are encouraged to take up Danish classes and reach an appropriate level of understanding.

Languages

ENGLISH

Level

Excellent

Number of offers available

1

Company/Institute

Geological Survey of Denmark and Greenland (GEUS)

Country

Denmark

City

Copenhagen

Postal Code

1350

Street

Oester Voldgade 10

Website

https://candidate.hr-manager.net/ApplicationInit.aspx?cid=5001&ProjectId=172449…

City

Copenhagen

Website

http://www.geus.dk/

Street

Øster Voldgade 10

Postal Code

1350

E-Mail

hcb@geus.dk