E-MUSE
Complex microbial Ecosystems MUltiScale modElling:
mechanistic and data driven approaches integration
Closed for Applications
JOB DESCRIPTION
Title
Early Stage Researcher (ESR4)
PhD fellowship in multi-omics data mining through (dynamic) mechanistic models
Project Title
“E-MUSE Complex microbial ecosystems multiscale modelling: mechanistic and data driven approaches integration” MSCA-ITN-2020 European Training Network
Hosting Organization
STICHTING VU (VUA), established in DE BOELELAAN 1105, AMSTERDAM 1081 HV, Netherlands, VAT number: NL851029279B01
Researcher Profiles
ESRs
Research Field
Food microbiology, molecular microbiology, cheese process, flavour formation, process modelling
Application Deadline
15th April 2021, 23:59 - Europe/Brussels time
Envisaged Job Starting Date
15.05.2021
Duration
3 years
Contract Type
full-time employment (based on COVID-19 evolution and restrictions, possibility to start remotely, once situation allows the presence is required)
Objectives
In this project, we will develop tools and methods to integrate dynamic multi-level omics data with genome-scale mechanistic models in the context of microbial communities. With partners in the E-MUSE Network (KUL, UNIBO, USZ, CHRH) we will explore (1) the use of machine-learning approaches for feature selection (for example SVM, Random forest, Ensemble techniques, etc.) for model development and prioritisation; (2) conversely the use of the mechanistic models and Individual-based Model as prior knowledge to constrain the search space in data-driven approaches. We will integrate the data into dynamic constraint-based ecosystem models, and apply the tools and methods to the biological study cases, i.e. the cheese ripening case and the growth physiology of associated microbial species.
Expected Results
We expect to deliver tools (open source software) and methods (algorithms, modelling strategies) to use multi-omics data to generate insight in the relevant interactions inside and between microorganisms in complex dynamic ecosystems. We will provide insight in the usefulness of combining machine-learning and mechanistic modelling approaches. Finally, we will provide, in collaboration with the network partners, specific models and predictions that will lead to a better understanding of the biological use cases.
Planned Secondments
In total, 2 months will be spent at the Agencia estatal Consejo superior de Investigaciones cientificas in Spain (dynamic optimisation technologies), 2 months at the Katholieke Universiteit Leuven in Belgium (modelling aspects) and 3 months at the Institut national de recherche pour l'agriculture, l'alimentation et l'environnement in France and at the Chr. Hansen A/S in Denmark (biological data).
Enrolment in Doctoral degree
Vrije Universiteit Amsterdam (VUA) (https://www.vu.nl/en)
Requirements
Required Education Level
MSc degree in Systems Biology, Bioinformatics, (Bio)physics, Engineering or Biology with a strong theoretical/computational component
Skills / Qualifications
• Independence, curiosity, open-mindedness, ability to (learn to) communicate with different disciplines (experimental, computational, theoretical) and will to understand complex systems
• Educational background and previous research experience relevant for the chosen position
• Networking and communication skills in a multicultural and multidisciplinary environment
• Willingness to travel abroad for the purpose of research, training and dissemination
Specific Requirements
For the eligibility please check: Eligibility Criteria
Required Languages
English: B2, good oral and written communication skills in English are compulsory
Supervisors Team
Host Institution Description
The lab of VUA, in which the proposed work will be carried out, studies the molecular networks inside cells that give rise to cell behavior and fitness, in isolation and in interaction with other cells and their environment. The team focuses on the principles and general understanding of how those networks adapt in response to environmental and genetic changes and combine mathematical modelling, theory, and experiments. The approach is to apply the fundamental insights and methods in a biotechnological and biomedical setting.
The lead supervisor is prof. dr. B. Teusink (VUA), the head of the Systems Bioinformatics group, which he runs together with prof. dr. F. Bruggeman (VUA) who is also one of the co-supervisors. B. Teusink's group currently houses 6 PhD students and 2 postdocs. Of previous students, 2 PhDs and 3 PDs now have a faculty position at Dutch Universities; 2 PhDs and 5 PDs moved to R&D jobs in industry, 3 PhDs are currently postdocs elsewhere, and 3 PhDs work as data analysts for bank and insurance companies. The co-supervisors for this role are also dr. D. Molenaar (VUA) - member of prof. Teusink group who is specialist in microbiology, bioinformatics and data analysis and J. Van Impe (KUL) - the Division Hear and founder of BioTeC (Chemical and Biochemical Process Technology and Control) research group at KU Leuven.
The Vrije Universiteit Amsterdam (VUA) is a university in Amsterdam, Netherlands, founded in 1880, and ranked among the world's top 150 universities by four major ranking tables. The VUA is one of two large, publicly funded research universities in the city of Amsterdam (https://www.vu.nl/en/index.aspx). The host Systems Biology Lab is headed by prof Bas Teusink and Frank Bruggeman and searches for the organizational principles of cellular behaviour. It develops and combines computational and experimental approaches to investigate the mechanisms and fitness consequences of gene expression regulation, metabolic strategies and growth. Its research spans different levels of organization, from single cells to cell cultures and microbial communities, and aims for fundamental understanding and apply it to different areas of application, like food, health, and biotechnology.