PhD student in spatial biodiversity modeling - Hiring in process/Finished, not possible to apply

The Department of Organismal Biology teaches and explores the evolution, development and function on the organismal level. For more information see www.iob.uu.se.

The Department is now looking for a 4-year PhD student, who will be based at the Evolutionary Biology Centre (EBC) at Uppsala University. The position is placed within the Biodiversity Data Lab (http://biodiversity.se), with Tobias Andermann as main supervisor.

At the Biodiversity Data Lab, we are working at the intersection of computational biology and biodiversity research, developing new computational methods and fieldwork/labwork workflows to quantify the complexity of biodiversity, mostly focusing on terrestrial systems. Our vision is to one day be able to reliably capture the complete biodiversity at a given site in a standardized and reproducible manner. We are a young and dynamic research group with a mission of contributing to alleviating the ongoing biodiversity crisis. We value innovative ideas, a collegial and non-hierarchical atmosphere, and high-quality and high-impact research. And above all we enjoy what we are doing!

Duties
This position will be focused on developing and implementing new computational and statistical approaches for the purpose of modeling biodiversity. An emphasis will be on developing solutions with a high utility for decision makers and other stakeholders. This will require dialogue with public agencies, national and international conservation networks, and/or the private sector. A background or experience in any of these fields is an additional merit that will be of benefit for this position.

Requirements
To meet the entry requirements for doctoral studies, you must

• hold a Master’s (second-cycle) degree in Biology, Data Science, Machine Learning, Statistics, or related fields, or
• have completed at least 240 credits in higher education, with at least 60 credits at Master’s level including an independent project worth at least 15 credits, or
• have acquired substantially equivalent knowledge in some other way.

The ideal candidate should have a good understanding of a) the nature and complexity of different types of biodiversity and earth observation data, b) the challenge of spatial modelling of biodiversity, c) the urgency of producing solutions applicable to decision makers, and d) the current state-of-the-art in this field. We value candidates who have an active interest in the dialogue about biodiversity solutions between academia, policy makers, and businesses.

Additional qualifications
We are looking for a highly motivated candidate who enjoys challenges and can independently explore new ideas, but also actively contribute to work in group settings. The ideal applicant has a background in working with biodiversity data, and has strong knowledge of statistics, programming (e.g. Python), commonly used machine learnings algorithms, and other data-driven methods. The candidate should have excellent communication skills (spoken and written English).

Rules governing PhD students are set out in the Higher Education Ordinance chapter 5, §§ 1-7 and in Uppsala University's rules and guidelines.

Application
The application should include 1) a letter of intent describing yourself, your research interests and motivation of why you want to do a PhD, 2) a short description of your education, 3) a CV, 4) a copy of your master degree and course grades, 5) the names and contact information (address, email address, and phone number) of at least two reference persons, 6) relevant publications (including master thesis). The application should be written in English.

About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 241101 or as agreed. Placement: Uppsala

For further information about the position, please contact: Tobias Andermann, 018-471 64 79, tobias.andermann@ebc.uu.se

Please submit your application by 27 september 2024, UFV-PA 2024/3078.

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