PhD position in data-driven biodiversity modeling in the Department of Organismal Biology teaches and explores the evolution
Uppsala University is a comprehensive research-intensive university with a strong international standing. Our ultimate goal is to conduct education and research of the highest quality and relevance to make a long-term difference in society. Our most important assets are all the individuals whose curiosity and dedication make Uppsala University one of Sweden’s most exciting workplaces. Uppsala University has over 54,000 students, more than 7,500 employees and a turnover of around SEK 8 billion.
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.
Read more about our benefits and what it is like to work at Uppsala University
The position is placed in the Andermann research group (https://katalog.uu.se/empinfo/?id=N22-999) within the Systematic Biology program at the Department of Organismal Biology (Evolutionary Biology Center, Uppsala University). The position will be part of the SciLifeLab Data-Driven Life Science (DDLS) research school (https://www.scilifelab.se/data-driven/about/), including unique training and course opportunities within the DDLS network.
At the Andermann lab, we are working on the intersect of computational biology and biodiversity research, developing new computational methods and fieldwork/labwork workflows to quantify the complexity of biodiversity, 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 the mission of contributing through our research 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/Project description
The main focus of this PhD position will be to develop AI models and/or other modeling approaches with the aim to predict the biodiversity capacity/potential of a given site. Although biodiversity is very complex, a good starting point is to focus on species richness or richness on other taxonomic levels. The training data for these models will be biodiversity data generated within our group as well as by local and international collaborators, largely consisting of genetic data resulting from environmental DNA sequencing. Sample datasets for initial development work are ready to be compiled and analyzed immediately. Predictors used in these models will consist of biotic as well as abiotic features, including high-resolution data generated by modern remote sensing techniques (e.g., satellite images and airborne laser scanning data).
Requirements
Completed university education of 240 university points (högskolepoäng, hp) of which at least 60 hp must be on advanced level, corresponding to a master’s degree in a relevant field. Relevant fields include biology, machine learning, data science, geosciences, remote sensing, bioinformatics, genomics, or related. We are looking for highly motivated candidates who enjoy challenges and can independently explore new ideas. The ideal applicant has a background in working with implementing machine learning models or other statistical models, and can demonstrate programming skills in Python, R, or similar. A research background in biological or geological sciences is desirable but interested students with a computer science or data science background are very welcome to apply as well. Candidates should have excellent communication skills (spoken and written English).
Additional qualifications
In filling this position, the university aims to recruit the person who, in the combined evaluation of competence, skills and documented qualifications, is judged most suitable to carry out and develop the work-in-hand and to contribute to a positive development of the department. Additional valuable qualifications include experience with remote sensing data, biodiversity metrics, and/or spatial analyses.
Position
The PhD-student position is a 4-year appointment, and the candidate will primarily devote the time to his/her own research studies. Other departmental work, such as teaching or administration can be part of the position (maximum 20 %, extending the position to a maximum of 5 years). Salary placement is in accordance with local guidelines at Uppsala University. The applicant must be eligible for PhD studies at Uppsala University.
Information about research education can be found at the web site of the Faculty of Science and Technology, https://www.teknat.uu.se/education/postgraduate/.
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 must be written in 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 http://regler.uu.se/?languageId=1.
About the employment
The employment is a temporary position according to the Higher Education Ordinance chapter 5 § 7. Scope of employment 100 %. Starting date 01-01-2023 or as agreed. Placement: Uppsala
For further information about the position, please contact: Tobias Andermann, tobias.andermann@ebc.uu.se.
Please submit your application by 31 august 2022, UFV-PA 2022/2451.
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Submit your application through Uppsala University’s recruitment system.
Placement: Department of Organismal Biology
Type of employment: Full time , Temporary position longer than 6 months
Pay: Fixed salary
Number of positions: 1
Working hours: 100 %
Town: Uppsala
County: Uppsala län
Country: Sweden
Union representative: ST/TCO tco@fackorg.uu.se
Seko Universitetsklubben seko@uadm.uu.se
Saco-rådet saco@uadm.uu.se
Number of reference: UFV-PA 2022/2451
Last application date: 2022-08-31