Research Assistant.
The fixed-term contract shall end on 30/06/2022. The position is suitable for part-time employment. Payment will be made according to pay group 13 TV-L Wissenschaft.
The position on offer is being provided within the research consortium DIG-IT!– "Digitisation of natural complexity for the solution of socially relevant ecological problems", as part of Mecklenburg-Vorpommern's research excellence programme "Digitisation in Research".
The DIG-IT! project:
DIG-IT! seeks to advance digitisation, in particular deep learning, making it accessible for use in ecological sciences. For this purpose, DIG-IT! combines the developmental expertise for the automated analysis of image data (Fraunhofer Institute for Computer Graphics, Rostock and Biomathematics University Greifswald), as well as the mathematical expertise of the Biomathematics and Stochastics research group, with the application of the results for tackling urgent ecological questions (Botany / Landscape Ecology / Zoology University Greifswald). More information can be found here: https://dig-it.uni-greifswald.de <https://dig-it.uni-greifswald.de/>
Job description:
DIG-IT! has been running since mid-2019, meaning that numerous digitisation tasks have already been concluded. The DIG-IT! consortium is thus able to access a broad variety of digitised data, ranging from bat images and bat sound recordings to tree cross-sections and pollen images and 3D root data. First analyses of this data has already been performed. The position advertised here, which belongs to the Biomathematics and Stochastics research group, shall now bring the understanding and findings gained from this data to a new level ("explorer" function). The postdoc shall ask and find the answers to new questions, which are only possible thanks to the new data: for instance, can the classification of bat image data be improved by also considering bat sound data or genetic data? Can 3D root growth be predicted if the distribution of nutrients in the soil is known? Can multidimensional data support the deep learning techniques in order to obtain useful presumptions?
There is an immense variety of mathematical, statistical and computer science questions in this project . The postdoc can therefore play an active role and make the most of his or her individual strengths and creativity in order to contribute to the level of knowledge gained by DIG-IT!. In particular, the postdoc is able to choose the mathematical and computer science tools and techniques used to tackle these questions in accordance with his/her strengths and interests.
The digitisation of image and acoustic data is not a core task of the position on offer. However, support with programme adjustment and possibly with the digitisation of some extra data are part of the job description. In particular, the successful candidate is expected to support PhD candidates with digital experience from the fields of both ecology and biomathematics with regard to aspects of machine learning.
Job requirements:
Completed PhD in (bio-)mathematics, bioinformatics, computer science or a closely related discipline
Mathematical experience, e.g. in the areas of graph theory and mathematical modelling
Sound knowledge of statistics
Knowledge in the area of machine learning
Mastery of at least one programming language; ideally Python
Excellent knowledge of the English language (both written and spoken)
Willingness to collaborate in an interdisciplinary team
Biological experience and German language proficiency are desirable, but not essential.
We are seeking a highly motivated candidate with outstanding qualifications, who is an enthusiastic and experienced researcher, and willing to contribute to this joint project.
This advertisement is directed at all persons, irrespective of gender.
The University would like to increase the proportion of women in areas in which they are underrepresented and thus applications from women are particularly welcome and will be treated with priority if they have the same qualifications and as long as there are no clear reasons which make a fellow applicant more suitable.
Severely disabled applicants with the same qualifications will be considered with preference.
In accordance with § 68(3) PersVG M-V, the Staff Council will only be involved in staff matters of the academic or artistic staff on request.
Please only submit copies of original documents with your application as these cannot be returned. Unfortunately, application costs (e.g. travel expenses for interviews) will not be reimbursed by the state of Mecklenburg-Vorpommern.
Applications comprising all usual documents (letter of motivation, curriculum vitae, copies of academic certificates, list of publications) should be sent by 7June 2020, via email (one PDF file), to:
Universität Greifswald
Institut für Mathematik und Informatik
Frau Prof. Dr. Mareike Fischer
Walther-Rathenau-Str. 47
17489 Greifswald
ag-fischer-biomathe@uni-greifswald.de <mailto:ag-fischer-biomathe@uni-greifswald.de>
Do not hesitate to contact me in case you have any questions!
The official announcement can be found here: https://www.uni-greifswald.de/en/university/information/jobs/job/n/wissenschaftlicher-mitarbeiterin-institut-fuer-mathematik-und-informatik-20sa17-64781/
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Prof. Dr. Mareike Fischer
Biomathematics and Stochastics
Institute for Mathematics & Computer Science
Greifswald University
Walther-Rathenau-Str. 47
Office 3.15
17487 Greifswald
GERMANY
+49 (0) 3834 420 46 43
mareike.fischer@uni-greifswald.de
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