91 Centre for Microbiology and Environmental Systems Science
Startdate: 01.09.2024 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1 Grundstufe (praedoc)
Limited until: permanent
Reference no.: 2850

Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced around 7,500 academic staff members so far. They see themselves as personalities who need space for their continuous striving and curiosity in order to be able to be scientifically successful. Does that sound like something for you? Welcome to our team!

Description of the position:

The Division of Microbial Ecology (DOME) within the Centre for Microbiology and Environmental Systems Science is offering an exciting opportunity for a University Assistant PraeDoc to obtain a PhD degree. We are a highly motivated international group carrying out research in environmental science and related fields. Our infrastructure provides a broad spectrum of possibilities to realize interdisciplinary research ideas. We are looking for a PhD student to work on projects that will bring us closer to identifying unifying themes driving microbiome variability, function, and evolution:

Large-scale data analysis and machine-learning across microbial ecosystems

Recent technological advances in DNA sequencing allow incredible feats such as sequencing individual cancer cells to characterizing the inventory of microbial species on a single grain of sand. The goal of this project is to develop efficient computational approaches that rely on modern machine-learning concepts to extract biological, ecological, and evolutionary knowledge from the large amount of sequencing data produced by the different work packages in the “MicroPlanet” Cluster of Excellence. Since the early 2000s petabytes of sequencing data have been produced, but the biological insights promised at the onset of the sequencing revolution have not been delivered yet. The sheer diversity of microbial life, with estimated billions of species and trillions of gene families limits our quest for insights, as most genes and species are uncharacterized, and it would take many decades of laborious experimentation to close this gap. Recent advances in Machine learning such as the advent of Large Language Models and tools like AlphaFold have exposed the utility of large-scale data analysis in breaking traditional barriers in biological research. The cluster of excellence offers a unique opportunity to synthesize large volumes of data from across ecosystems to answer fundamental biological questions, but efficient computational tools that go beyond the state-of-the-art are still needed for this task. This project will be in close collaboration with the experimental labs in the Cluster of Excellence and will develop new approaches and tools to analyze time-series data, bacterial genomic data, protein variation and evolution, and making theory-guided inferences about ecology from the underlying genetic and taxonomic structure of microbial communities. Candidates from Computer Science / Physics / Mathematics background with experience in machine-learning are encouraged to apply.

Your future tasks:

• We expect the successful candidate to sign a doctoral thesis agreement within 12-18 months and to participate in research, teaching, and administration throughout the employment, specifically:
• Participation in research projects as part of the Cluster of Excellence synthesis module
• Publishing/presenting research in international top journals/conferences 
• Teaching as defined by the collective agreement
• Supervision of students
• Developing an independent research profile

This is part of your personality:

• M.Sc. Degree in a relevant field (Physics/Computer Science/Mathematics/Ecology)
• Advanced knowledge in Machine-Learning / analysis of complex systems using tools from statistical physics
• Excellent command of written and spoken English
• Willingness and ability to work as part of a diverse and international team 
• Curious, independent, proactive, and motivated personality

What we offer:

Work-life balance: Our employees enjoy flexible, family-friendly working hours, remote/hybrid and/or part-time work (upon agreement)

Inspiring working atmosphere: You are a part of an international academic team in a healthy and fair working environment.

Good public transport connections: Your workplace in the center of beautiful Vienna is easily accessible by public transport.

Internal further training & Coaching: Opportunity to deepen your skills on an ongoing basis. There are over 600 courses to choose from – free of charge.

Fair salary: The basic salary of EUR 3578,80  (on a full-time basis) increases if we can credit professional experience.

Equal opportunities for everyone: We look forward to diverse personalities in the team!

The employment duration is 4 years. Initially limited to 1.5 years, the employment relationship is automatically extended to 4 years if the employer does not terminate it within the first 12 months by submitting a non-extension declaration.

It is that easy to apply:

Please submit the following documents through our job portal ("Apply now" button):

• Letter of motivation 
• Academic curriculum vitae 
• Master Degree / Diploma

If you have any questions, please contact:

Shaul Pollak Pasternak

shaul.pollak.pasternak@univie.ac.at

We look forward to new personalities in our team! 
The University of Vienna has an anti-discriminatory employment policy and attaches great importance to equal opportunities, the advancement of women and diversity. We lay special emphasis on increasing the number of women in senior and in academic positions among the academic and general university staff and therefore expressly encourage qualified women to apply. Given equal qualifications, preference will be given to female candidates.

University of Vienna. Space for personalities. Since 1365.

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​Application deadline: 08/09/2024 

Prae Doc