PhD Position in Benchmarks for Spatial Optimisation

Are you interested in spatial optimisation algorithms? And do multi-objective optimisation problems in spatial planning and economic geography draw your attention? Do you advocate for free and open source software? Do you program in Python and/or R? Then this job at the department of Human Geography and Spatial Planning is perfect for you!

Your job

The transition towards a sustainable and livable urban future requires resolving multiple issues. Potential solutions for these issues may be compatible (synergies), or may conflict (trade-offs). For example, under the current pressing housing demand, the objective to maximise peri-urban landscape biodiversity and food provision results in high residential densities within the existing urban fabric. This may conflict with the objectives to minimise the decline of open space and the congestion and air pollution in the city. Quantifying synergies and trade-offs between these objectives can serve the spatial planning process. Multi-objective spatial optimisation algorithms offer such quantification.

The aim of this project is to improve the comparability and selection of spatial optimisation algorithms through the design, testing, and publication of spatial optimisation benchmarks. Benchmark problems or benchmarks are standardised tests used in the computer sciences for the evaluation, characterisation and performance measurement of algorithms, software packages, or hardware.

This project both solves a conceptual Geo-Information-Science challenge, and extensively uses domain-specific knowledge to provide easily re-usable solutions for domain experts in various geography (sub)domains. In this project, you will:

• collect a variety of spatial optimisation problems, mainly related to spatial planning and economic geography, from literature as well as from discussions with domain experts;
• develop methods to cluster them based on their characteristics (e.g. the shape of the solution space);
• design representative benchmark problems for each of these clusters that can help to quickly identify the quality of optimisation algorithms for solving them;
• test these benchmarks on domain-specific optimisation problems; and make the benchmark problems available as free and open source software.

Your qualities

We are looking for someone with:

• an MSc degree in Geoinformatics, Computer Science, (Quantitative) Geography, (Spatial / Geographic) Data Science, Environmental Science, or a related discipline;
• an interest in spatial planning and economic geography;
• experience in handling spatial data;
• programming skills in Python, and/or R;
• proficiency in English;
• strong communication skills;
• the ability to work independently and as part of a research team.

Our offer

We offer:

• a position 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.
• a working week of 36 hours and a gross monthly salary between €2,770 and €3,539 in the case of full-time employment (salary scale P under the Collective Labour Agreement for Dutch Universities (CAO NU));
• 8% holiday pay and 8.3% year-end bonus;
• a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.