Ongeveer 10 uur geleden - Universiteit van Amsterdam (UvA) - Amsterdam
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Project Description Many industrial biotechnological processes are carried out by consortia of bacteria, rather than single strains. To improve performances of such processes, the biotech industry currently relies mostly on screening-based selection of isolated strains ...
Many industrial biotechnological processes are carried out by consortia of bacteria, rather than single strains. To improve performances of such processes, the biotech industry currently relies mostly on screening-based selection of isolated strains with desired properties. However, these properties are very often influenced by other consortium members in unknown ways. Screening consortia is challenging, because only a tiny subset of all the many possible combinations can ever be tested. There is therefore a need to develop methods that can predict performance of strains in consortia, on the basis of the genome and selected phenotypic traits. This project aims to develop an integrative bioinformatics and modelling approach to predict microbial community functioning from the properties of the constituent isolates.
We will do this through a real industrial use case: the design of microbial cultures for the production of yogurt. Industrial-scale yogurt production is carried out with a broad range of cultures consisting mainly of Streptococcus thermophilus and Lactobacillus delbrueckii ssp. bulgaricus strains. Different cultures (a blend of typically 2 to 5 different strains) are formulated to obtain desirable characteristics in the final product, such as fast acidification to a desired acidity, optimal texture, reduced fat levels, proper sweetness or desired flavour profile. Understanding the genetic determinants of variability between strains related to such functionalities is a key question in the industry. However, the overall function of milk-fermenting strains can largely be modulated by the metabolic interactions between the individual strains. Yogurt fermentation therefore is an excellent test case to develop rational community designer methods, as it consists of relatively few species and its interactions and industrially-relevant properties are based on metabolism – an area amenable to rigorous experimental and computational analyses.
The PhD candidate at the VU will develop and apply different computational approaches, including constraint-based methods for ecosystems, metabolic reconstructions and data-driven (machine-learning) methods. Strong interaction with the experimental groups will be essential.
We are looking for a highly motivated, critical, and ambitious postdoctoral researcher with a background and experience in computer science (bioinformatics), (bio)physics or (computational) systems biology. You are eager to work in a research consortium in a multidisciplinary and dynamic setting. You are flexible and willing to travel and work in different labs.
The appointment will be for a period of 1 year with potential for extension to a total duration of 3.5 years.
Information about our excellent fringe benefits of employment are for example:
• a wide range of sports facilities which staff may use at a modest charge;
• remuneration of 8,3% end-of-year bonus and 8% holiday allowance;
• generous commuting allowance;
• discounts on collective insurances (healthcare- and car insurance).
We aim to start the project on the 1st of March 2018.
The salary will be in accordance with university regulations for academic personnel.