PhD Position in Benchmarks for Spatial Optimisation

Faculty:

Faculty of Geosciences

Department:

Department of Human Geography and Spatial Planning

Hours per week:

36 to 40

Application deadline:

1 July 2024 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 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. We are looking for someone with: an MSc degreein 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; the ability to work independently and as part of a research team. Our offer

We offer: a positionfor 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 of36hours and a gross monthly salary between €2,770and €3,539in 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. 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 external link

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 degreein 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 positionfor 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 of36hours and a gross monthly salary between €2,770and €3,539in 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. In addition to the terms of employment external link

laid down in the CAO NU, Utrecht University has a number of schemes and facilities of its own for employees. This includes schemes facilitating professional development

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, leave schemes and schemes for sports and cultural activities

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, as well as discounts on software and other IT products. We also offer access to additional employee benefits through our Terms of Employment Options Model. In this way, we encourage our employees to continue to invest in their growth. For more information, please visit Working at Utrecht University

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. About us

A better future for everyone. This ambition motivates our scientists in executing their leading research and inspiring teaching. At Utrecht University external link

, the various disciplines collaborate intensively towards major strategic themes

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. Our focus is on Dynamics of Youth, Institutions for Open Societies, Life Sciences and Pathways to Sustainability. Sharing science, shaping tomorrow

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. Utrecht University’s

Faculty of Geosciences external link

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 department of Human Geography and Spatial Planning external link

investigates sustainability challenges in the context of an ongoing worldwide trend of increasing urbanisation. The department’s ‘Urban Futures’ research programme focuses on urban inequalities, geographies of digital transitions, and urban environmental change. It develops novel theoretical and empirical approaches that are not solely at the forefront of academic debates but that also create new perspectives on successful policies and interventions to address urban challenges. Our research programme is the basis for our Research Master's Human Geography and Geographical Information Management and Applications and for our Professional Master's in Spatial Planning, Human Geography and International Development Studies. The department also runs a large and highly appreciated Bachelor's programme and is part of the Netherlands Graduate School of Urban and Regional Research for PhD candidates. Unique characteristics of the department are a special team focusing on innovations within teaching methods, its strong involvement in the transdisciplinary sustainability research theme and professional consultancy for public partners. More information

For more information, please contact

Dr Judith Verstegen external link

at j.a.verstegen@uu.nl.

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Candidates for this vacancy will be recruited by Utrecht University. Apply now

As Utrecht University, we want to be a home external link

for everyone. We value staff with diverse backgrounds, perspectives and identities, including cultural, religious or ethnic background, gender, sexual orientation, disability or age. We strive to create a safe and inclusive environment in which everyone can flourish and contribute. To apply, please send your curriculum vitae, including a letter of motivation, via the ‘apply now’ button. The first round of interviews will take place in the week of 15 July. The aimed starting date is 1 October2024. The application deadline is 1 July 2024.

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