The University of Helsinki, founded in 1640, is one of the world’s leading universities for multidisciplinary research. The University of Helsinki has an international academic community of 40,000 students and staff members, and it offers comprehensive services to its employees, including occupational health care and health insurance, sports facilities, and opportunities for professional development. The International Staff Services (https://www.helsinki.fi/en/university/working-at-the-university) office assists employees from abroad with their transition to work and life in Finland. The Organismal and Evolutionary Biology Research Programme is situated at the Viikki science park and belongs to the Faculty of Biological and Environmental Sciences of University of Helsinki.

The Organismal and Evolutionary Biology Research Programme (OEB) invites applications for

TWO POSTDOCTORAL RESEARCHERS AND/OR PHD STUDENTS

in the field of statistical ecology for a fixed term of three years for a postdoctoral researcher or four years for a PhD student. There will be a trial period of six months in the beginning.

The postdoc position is part of the LIFEPLAN project funded by an ERC Synergy grant to Prof. Otso Ovaskainen at the University of Helsinki, Prof.Tomas Roslin at the Swedish University of Agricultural Sciences in Uppsala, Sweden, and Prof. David Dunson at Duke University, USA. The starting date is 1 April 2020, but a later or earlier starting date can be negotiated.

The overarching aim of LIFEPLAN is to characterize biological diversity through a worldwide sampling program, and develop the bioinformatic and statistical approaches needed to make the most out of these data. We will generate the most ambitious, globally distributed and systematically collected data set to date on a broad range of taxonomical groups. For more information please visit our website (https://www.helsinki.fi/en/projects/lifeplan).

The statistical ecology positions are aimed at developing methods that help better interpret the massive data to be collected by the LIFEPLAN sampling scheme (https://www.helsinki.fi/en/projects/lifeplan/lifeplan-global-sampling-plan). One application area is the development of automated methods for identifying species from DNA, audio and image data. For our previous work in this area, see e.g. Abarenkov et al. (2018), Abrego et al. (2018), Ji et al. (2020), Ovaskainen et al. (2018, 2020), and Somervuo et al. (2016, 2017).

Another application area is the development of statistical methods for analysing large-scale data on species communities, especially by (but not restricted to) joint species distribution modelling. For our previous work in this area, see e.g. Norberg et al. (2019), Ovaskainen et al (2017, 2019) and Tikhonov et al. (2020a, 2020b).

The candidates may have their background in statistics, computer science or quantitative ecology. In particular, we appreciate experience in working with large and complex datasets, expertise in Bayesian inference, as well as programming skills (in particular in the R-environment).

For more information, contact prof. Otso Ovaskainen (otso.ovaskainen(at)helsinki.fi).

For a postdoctoral researcher, the salary of the successful candidate will be based on level 5 - 6 of the demands level chart for teaching and research personnel in the salary system of Finnish universities. In addition, the appointee will be paid a salary component based on personal performance. The starting salary will be ca. 3300 - 3800 euros/month, depending on the appointee’s qualifications and experience.

The salary for the doctoral candidate position is based on levels 2–4 of the job requirement scheme for teaching and research personnel in the salary system of Finnish universities. In addition, the appointee will be paid a salary component based on personal work performance. Depending on the appointee’s qualifications and experience, the salary is ca EUR 2200–3050 per month (starting salary EUR 2200-2400).

Applications should include the following documents as a single pdf file: motivational letter (max 1 page), CV (max 2 pages) and publication list. Include also contact information of two persons who can provide a reference letter upon request.

Please submit your application using the University of Helsinki Recruitment System via the Apply for the position link. Applicants who are employees of the University of Helsinki are requested to leave their application via the SAP HR portal. The deadline for submitting the application is 1 March 2020.

References
Abarenkov, K., Somervuo, P., Nilsson, H., Kirk, P., Huotari, T., Abrego, N. and Ovaskainen, O. 2018. PROTAX-fungi: a web-based tool for probabilistic taxonomic placement of fungal ITS sequences. New Phytologist 220, 517-525. https://doi.org/10.1111/nph.15301

Abrego, N., Norros, V., Halme, P., Somervuo, P., Ali-Kovero, H. and Ovaskainen, O. 2018. Give me a sample of air and I will tell which species are found from your region – molecular identification of fungi from airborne spore samples. Molecular Ecology Resources 18, 511-524. https://doi.org/10.1111/1755-0998.12755

Ji, Y., Huotari, T., Roslin, T., Schmidt, N. M.,Wang, J, Yu, D. W. and Ovaskainen, O. 2020. SPIKEPIPE: A metagenomic pipeline for the accurate quantification of eukaryotic species occurrences and intraspecific abundance change using DNA barcodes or mitogenomes. Molecular Ecology Resources 20, 256-267. https://doi.org/10.1111/1755-0998.13057

Norberg, A., Abrego, N., Blanchet, F. G., Adler, F., Anderson, B., Anttila, J., Araújo, M., Dallas, T., Dunson, D., Elith, J., Foster, S., Fox, R., Franklin, J., Godsoe, W., Guisan, A., O'Hara, B., Hill, N., Holt, R. D., Hui, F., Husby, M., Kålås, J., Lehikoinen, A., Luoto, M., Mod, H., Newell, G., Renner, I., Roslin, T., Soininen, J., Thuiller, W., Vanhatalo, J., Warton, D., White, M., Zimmermann, N., Gravel, D. and Ovaskainen, O. 2019. A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels. Ecological Monographs 89, e01370. https://doi.org/10.1002/ecm.1370

Ovaskainen, O., Tikhonov, G., Norberg, A., Blanchet, F. G., Duan, L., Dunson, D., Roslin, T. and Abrego, N. 2017. How to make more out of community data? A conceptual framework and its implementation as models and software. Ecology Letters 20, 561-576. https://doi.org/10.1111/ele.12757
Ovaskainen, O., de Camargo, U. and Somervuo, P. 2018. Animal Sound Identifier (ASI): software for automated identification of vocal animals. Ecology Letters 21, 1244-1254. https://doi.org/10.1111/ele.13092

Ovaskainen, O., Rybicki, J. and Abrego, N. 2019. What can observational data reveal about metacommunity processes? Ecography 42, 1877-1886. https://doi.org/10.1111/ecog.04444

Ovaskainen,O., Abrego, N., Somervuo, P., Palorinne, I., Hardwick, B., Pitkänen, J.-M., Andrew, N. R., Niklaus, P. A, Schmidt, N. M., Seibold, S., Vogt, J., Zakharov, E. V., Hebert, P. D. N., Roslin, T. and Ivanova, N. V. 2020. Monitoring fungal communities with the Global Spore Sampling Project. Frontiers in Ecology and Evolution 7, 511. https://doi.org/10.3389/fevo.2019.00511

Somervuo, P., Koskela, S., Pennanen, J., Nilsson, H. and Ovaskainen, O. 2016. Unbiased probabilistic taxonomic classification for DNA barcoding. Bioinformatics 32, 2920-2927. https://doi.org/10.1093/bioinformatics/btw346

Somervuo, P., Yu, D., Xu, C., Ji, Y., Hultman, J., Wirta, H. and Ovaskainen, O. 2017. Quantifying uncertainty of taxonomic placement in DNA barcoding and metabarcoding. Methods in Ecology and Evolution 8, 398-407. https://doi.org/10.1111/2041-210X.12721

Tikhonov, G., Duan, L., Abrego, N., Newell, G., White, M., Dunson, D. and Ovaskainen, O. 2020a. Computationally efficient joint species distribution modelling of big spatial data. Ecology, in early view, https://doi.org/10.1002/ecy.2929. https://doi.org/10.1002/ecy.2929

Tikhonov, G., Opedal, Ø. H., Abrego, N., Lehikoinen, A., de Jonge, M. M., Oksanen, J. and Ovaskainen, O. 2020b. Joint species distribution modelling with the R-package Hmsc. Methods in Ecology and Evolution, in early view, https://doi.org/10.1111/2041-210X.13345

Due date

01.03.2020 23:59 EET