Doctoral student in environmental science: Robust analysis - Hiring in process/Finished, not possible to apply

Location
Center for Environmental and Climate Research, Lund University and also associated with the Biodiversity unit at Department of Biology.

Project description
The aim of this project is to develop, apply and evaluate principles of “Robust analysis” in risk-informed and evidence-based decision making. Robust analysis refers to a principle of that is used in the modelling and treatment of severe uncertainty. It is part of the PhD project to define and discuss uses of Robust analysis. In particular, the project will focus on Robust (or generalised) Bayesian analysis as a framework for considering qualitative uncertainty in quantitative assessments.

The project will use case studies from environmental management with high relevance to current policy, such as the European Common Agricultural Policy, and the EU Directive of Invasive Alien Species. The student will be part of an inter-disciplinary research environment with expertise and experience in ecological processes and policy measures associated with the case-studies.

This is a PhD project in Environmental science that combines applied statistics and mathematics with quantitative ecology, environmental management and risk analysis. The position is placed at the Lund University Center for Environmental and Climate Research and the Biodiversity unit at Department of Biology. In order to meet the demands of the cross-disciplinary nature of this PhD-project, the student will get supervision from Environmental Science (Ullrika Sahlin), Biology (Henrik Smith), Applied Statistics (Johan Lindström and Matthias Troffaes, Department of Mathematical Sciences, Durham University, United Kingdom), and Philosophy (Nils-Eric Sahlin, Department of Medical Ethics, Faculty of Medicine, Lund University).

The PhD students in Environmental Science are located at different departments at the faculty of Science. The PhD education will thus include interactions with other PhD students across subjects and departments.

Required qualifications
A Master’s degree in mathematics, biology, environmental science, or equivalent is required, and it must include relevant knowledge in statistical modelling. You should have documented experience of quantitative uncertainty analyses in a Master project, or equivalent, and a documented capacity to work independently. Participation in courses regarding decision theory, risk analysis, and Bayesian analysis are valued high in the evaluation.

An interest in applied statistics in general, and risk-informed and evidence-based environmental management in particular, is an advantage. The student is expected to work with case studies on robust analysis to consider uncertainty when managing alien invasive species and for meta-analysis of interventions in agricultural landscapes to enhance services provided by e.g. pollinators. Detailed knowledge of these problems is not a requirement. Instead, the applicant is expected to acquire the basic knowledge of invasive species biology, the ecosystem services framework and agricultural policy measures during the PhD-studies.

To be able to read and write academic texts in English is a requirement. Important qualifications are creative problem solving ability, to take responsibility for and finish projects independently, programming, and an interest to interact with stakeholders.

Eligibility
Students with basic eligibility for third-cycle studies are those who - have completed a second cycle degree - have completed courses of at least 240 credits, of which at least 60 credits are from second-cycle courses, or - have acquired largely equivalent knowledge in some other way, in Sweden or abroad.

The employment of doctoral students is regulated in the Swedish Code of Statues 1998: 80. Only those who are or have been admitted to PhD-studies may be appointed to doctoral studentships. When an appointment to a doctoral studentship is made, the ability of the student to benefit from PhD-studies shall primarily be taken into account. In addition to devoting themselves to their studies, those appointed to doctoral studentships may be required to work with educational tasks, research and administration, in accordance with specific regulations in the ordinance. Other tasks should account for no more that 20% of time and grants a corresponding extension of the study period.

Type of employment

Limit of tenure, four years according to HF 5 kap 7§.