Postdoc position in bioinformatics & spatial modeling using metabarcoding data - 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 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 on the intersect 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 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
Metabarcoding of environmental DNA samples provides unprecedented opportunities for biodiversity research, as it offers comprehensive biodiversity inventories of a given site across the whole tree of life. Despite some existing methodological limitations leading to biases in species detection, these data represent a true revolution in biodiversity assessments, as for the first time we are able to detect the large hidden diversity of undescribed and taxonomically inconspicuous species, making up more than 80% of all species on this planet. In this project we will harness the potential of these data and utilize them in traditional statistical models for species distribution modeling and modeling of species richness. We will also explore the potential of new deep learning approaches, building up on custom models developed in our previous and ongoing research at the Biodiversity Data Lab.

More specifically the project will consist of the following major steps:

• Data mining and organization of metabarcoding data from public databases and dataset provided by collaborators
• Processing metabarcoding datasets using internal bioinformatic pipeline (this pipeline is already fully functional, but may require specific adaptations for some datasets)
• Extracting geographic information from individual species/ASV sequences from metabarcoding datasets, including presences and absences
• Compiling environmental predictors, including remote sensing data (using our existing pipeline you will have access to >60 environmental predictors for any given site)
• Species distribution modeling using conventional methods as well as custom-built neural network approaches (in case this matches candidate's background and/or interest)

We already explored the feasibility of this project with a small pilot study where we compiled more than 2000 metabarcoding samples, showing promising results. Your role will be to lead the project including the steps listed above, and lead the publication of the results as first author. During the whole project duration, you will have access to domain knowledge on metabarcoding data from other members of the Biodiversity Data Lab, to methodological expertise through our AI consultant, and to bioinformatic support from the NBIS support center, if needed. We are excited to have you join our team!

The candidate will primarily devote the time to his/her own research. Other departmental work, such as teaching or administration can be part of the position, based on interest and availability (maximum 20% of fulltime, extending the position-duration accordingly). The applicant must be eligible for a postdoctoral position at Uppsala University. 

Requirements
PhD degree in biology or a foreign degree equivalent to a PhD degree in biology. The degree needs to be obtained by the time of the decision of employment. Those who have obtained a PhD degree less than three years prior to the application deadline are primarily considered for the employment. The starting point of the three-year period is the application deadline. The three-year period can be extended due to circumstances such as sick leave, parental leave, duties in labour unions, etc.

We are looking for a highly motivated candidate who enjoys challenges and can independently explore new ideas. The ideal applicant has a background in working with genomic data, preferably within the context of eDNA, and should be comfortable with bioinformatics and basic statistics. The candidate 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 coding experience in Python, R, or similar, as well as experience with working on computing clusters. Experience with species distribution modelling and/or other spatial analyses are additional merits that are relevant for the position.

Application
The application should include 1) a letter of intent describing yourself, your research interests and motivation of why you are applying for this position, 2) a short description of your education, 3) a CV, 4) a copy of your PhD 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 PhD thesis). The application should be written in English.

About the employment
The employment is a temporary position of at least two years and at most three years
 years according to central collective agreement. Scope of employment 100 %. Starting date 2024-04-01 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 29 February 2024, UFV-PA 2024/380.

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