PhD position: Dynamics of environmental heterogeneity and species diversity across scales – Deadline 05 November 2023

Overview

Environmental heterogeneity (EH), covering the heterogeneity of vegetation, land cover, soil, topography and climate, is a key factor determining biodiversity patterns and ecosystem processes. We need accurate EH data to understand the mechanisms driving diversity loss and generate solutions to bend the biodiversity curve. We also need the dynamics of EH at different spatial scales to understand why the change of biodiversity differ at local, regional, and global scales.

However, a lack of accurate spatial quantification of EH and their change over time have hampered our understanding of the driving mechanisms and their application in biodiversity conservation. Recent developments in Remote Sensing (RS) techniques and the accumulation of high-resolution RS data (e.g., vegetation structure) over time offer the opportunity to quantify EH more accurately.

The goal of the project is to develop a methodological framework to accurately quantify the dynamics of environmental heterogeneity and apply it to specific ecosystems (e.g., terrestrial, aquatic, urban or agricultural systems) to further our understanding of the mechanisms shaping the spatiotemporal patterns of diversity. Moreover, a case study will be carried out to develop landscape-specific measures to maintain or restore specific species diversity (e.g., bird diversity).

The appointed candidate will work closely with a multidisciplinary team including academic staff from multiple fields (e.g., ecology, RS, and environmental sciences) and relevant PhD candidates. The candidate will learn and utilize knowledge and methodology from different fields and gain multidisciplinary skills.

Key tasks

• Integrate multi-source data to quantify the dynamics of environmental heterogeneity (EH) across space and time
• Analyze the relationships between the dynamics of EH and species diversity
• Apply the knowledge to develop landscape management measures to maintain/restore targeted species communities

Selection criteria

• A M.Sc. degree in a relevant field (e.g. ecology, environmental sciences, geo-information systems, RS, and biology,), but we also consider candidates from other scientific fields with good quantitative skills and an interest in studying the dynamics of environmental heterogeneity.
• Quantitative analysis, programming, and statistical skills are preferred
• Experiences in working with large datasets (e.g., RS data) or using high performance computation platforms are preferred. We also consider candidates that have basic knowledge in remote sensing data analyses and willing to further develop it.
• Proficiency in spoken and written English and good communication skills
• Team player and having a collaborative attitude

Leiden University offers an attractive benefits package with additional holiday (8%) and end-of-year bonuses (8.3 %), training and career development and sabbatical leave. Our individual choices model gives you some freedom to assemble your own set of terms and conditions. For international spouses we have set up a dual career program. Candidates from outside the Netherlands may be eligible for a substantial tax break.

Diversity

Leiden University is strongly committed to diversity within its community and especially welcomes applications from members of underrepresented groups.

Coming from abroad

Leiden University is an international work place. Applicants from abroad moving to the Netherlands may qualify for a special tax relief, known as the 30% ruling. Our team of advisors on Dutch immigration procedures will help you with the visa application procedures for yourself and, if applicable, for your family. Our Service center for international staff will help you on the way and make you feel welcome to Leiden.

For more information

Applications

To apply for this vacancy, please send an email to sollicitaties@cml.leidenuniv.nl . Please ensure that you upload the following additional documents quoting the vacancy number:

• A motivation letter (max 1 page)
• CV (max 2 pages) including names and contact details of two references
• A scientific writing sample (max 1 page; could be part of your thesis or reports)

Only applications received before the 6th of November will be considered. Interview will take place between November 13-17. Preferred starting date is January 1, 2024.