Postdoctor in deep learning solutions in paleobiology
Göteborgs universitet / Biologjobb / Göteborg
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hela Sverige The University of Gothenburg tackles society's challenges with diverse knowledge. 49 000 students and 6 400 employees make the university a large and inspiring place to work and study. Strong research and attractive study programmes attract scientists and students from around the world. With new knowledge and new perspectives, the University contributes to a better future.
At the Department of Biological and Environmental Sciences (BioEnv) we have teaching and research activities that stretch from the alpine ecosystem, through forests, cultivated land and streams, all the way into the marine environment. In these environments we study different levels of biological organization from genes, individuals and populations, to communities and ecosystems. We work within ecology, evolution, physiology, systematics and combinations of these fields in order to understand the impact of natural and anthropogenic changes of the environment.
The Department of Biological and Environmental Science (
http://bioenv.gu.se) is the host of the Gothenburg Global Biodiversity Centre (GGBC,
http://ggbc.gu.se). The Centre has two main goals: to further develop biodiversity research, and to bridge the gap between scientists, the public and industry. The working language is English.
The department is placed at three different localities: in Gothenburg Botanical garden, at Medicinarberget in Gothenburg, and Kristineberg Marine Research Station. The current position is placed at Gothenburg Botanical garden with flexibility for spending time in Switzerland (University of Fribourg). Whenever possible, international collaborations will be carried out through video-conferencing to reduce environmental impact.
Project description
The goal of the project is to channel the power of deep learning algorithms for evolutionary biology research. A focus of the project will be on developing Bayesian neural network models for classification and regression within the context of inferring biome evolution through time and space, combining all available evidence ranging from the fossil record to geological measurements and proxies. Beyond the empirical application of the deep learning model to infer paleo-environmental changes, the project also aims to implement and release programming libraries that can be applied to a wide range of research projects. In general, the conducted research is expected to link with the Principal Investigator broad areas of research, which include Bayesian algorithms, models of species diversification, dispersal and extinction, models of phenotypic evolution, and the statistical analysis of paleontological and phylogenetic data across different taxonomic groups.
This project will be primarily supervised by Daniele Silvestro (University of Fribourg, University of Gothenburg, and GGBC), and further interactions and collaborations within the vibrant research environment provided by the GGBC are highly encouraged. The work may include research visits to the University of Fribourg, Switzerland.
Job assignments
This employment includes the following tasks: conducting independent and collaborative research; responsibility for managing own workload; production of scientific articles and software; effective communication including in seminars and conferences.
Eligibility
The applicant must hold a PhD degree in an area relevant for the tasks at hand (e.g., computational biology, evolutionary biology) or a foreign exam substantially equivalent to a PhD degree in a relevant subject. Preference will be given to candidates who have been awarded the degree no more than two years before the application deadline. Applicants with a degree awarded earlier may also be preferred if specific reasons exist. Such specific reasons may be a leave due to illness, parental leave or other similar circumstances. Applicants are eligible as long as all necessary requirements for a PhD degree are successfully completed at the application closing date, even if the awarding of the PhD degree is still pending.
Assessments
We are seeking a highly motivated person engaged in research in evolutionary and computational biology and able to take a leading role in this project.
The following skills are crucial for this employment:
• PhD Degree, or equivalent, within biology, bioinformatics, or computer science
• Excellent ability to communicate in spoken and written English (ability to communicate in Swedish is not a requirement)
• Demonstrated experience with Python programming
• Documented background (publications, teaching experience) in machine learning and Bayesian statistics
• Excellent collaborative skills but also be ability to work independently
• Experience of speaking in front of others and giving presentations.
We will consider the following additional criteria:
• Track record of the applicant (scientific publications and software, if applicable)
• Technical skills (e.g., published programs, GitHub repositories)
• Background in bioinformatics and/or paleobiology
Employment
The employment is a full-time position for two years placed at the Department of Biological and Environmental Science.
For further information and how to apply
In order to apply for a position at the University of Gothenburg, you have to register an account in our online recruitment system. It is the responsibility of the applicant to ensure that the application is complete in accordance with the instructions in the job advertisement, and that it is submitted before the deadline. The selection of candidates is made on the basis of the qualifications registered in the application.
In connection to this recruitment, we have already decided which recruitment channels we should use. We therefore decline further contact with vendors, recruitment and staffing companies.
Varaktighet, arbetstid
Heltid/ Ej specificerat
Publiceringsdatum2020-11-30ErsättningIndividuell lönesättning
Så ansöker duSista dag att ansöka är 2020-12-21
Klicka på denna länk för att göra din ansökanFöretagGöteborgs Universitet
Omfattning Detta är ett heltidsjobb.
Arbetsgivare Göteborgs Universitet (org.nr 202100-3153),
http://www.gu.se/ Arbetsplats Göteborgs universitet
Jobbnummer 5468158
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