This 3-year postdoc position is part of a larger European collaboration in the Horizon 2020 programme.

We are seeking a postdoctoral researcher to work on an innovative research project in a highly interdisciplinary team. For this project you will focus on the use of mathematical and computational methods to expand the concept and applicability of disease networks, both theoretically and computationally. The main objective is to achieve the ability to combine multiple datasets, such as clinical cohort studies, and data types (e.g., genomics, proteomics, exposome) into a single analysis of multi-morbidity disease states. These analyses specifically focus on the link between cardiovascular diseases and clinical depression as two often intertwined diseases states.

There is a growing consensus that the complexities underlying the onset of disease of an individual cannot be understood by traditional, reductionistic methods alone. A shift in research paradigm towards complex systems, network thinking, and multivariate analysis is considered imperative to move this field forward. In particular, a major challenge in the management of disease states is multi-morbidity, i.e., the presence of two or more diseases at the same time. Patients with multiple diseases are more difficult to treat, but the pathways underlying multi-morbid states are poorly understand.

Project and job description

The EU project, of which you will be part, is centered around well-phenotyped longitudinal patient cohorts and population studies, containing a large amount of clinical and epidemiological information on cardiovascular disease and depression, including risk factors, metabolic and mental comorbidities, multiple omics datasets (including genomics, epigenomics, transcriptomics, lipidomics/metabolomics and targeted proteomics already available) and other biomarkers. These data are generated over the years through investments at the national and European level and provide a unique opportunity. In order to characterize the biological pathways and networks associated with CVD-depression multimorbidities these data will be explored through the application of multidimensional state-of-the-art methodologies combining bioinformatics, computational biology, mathematics and statistics, new algorithms and systems medicine approaches, with the aim to unwind shared causative mechanisms and identify novel biomarkers. These analyses will be complemented by studies of monocyte/macrophage/microglial function in patients’ cells in the laboratory and experimental animal and cell-based models in order to confirm causality and further refine the molecular mechanisms involved.

You will focus specifically on identifying as well as modeling (mathematical/computational) the dynamics of multi-morbidities. This will be done through extending the concept of disease networks (see for instance this article for an accessible introduction and relevant references). The first manner in which we plan to extend it is to enrich the statistical associations, used as part of the method, with multivariate information-theoretic measures, specifically the novel concept of synergistic information (see for instance this article). The second manner is to extend the network concept to a multiplex network, due to integrating different types of studies into a single analysis. Finally, we will attempt to identify causal links and causally important nodes in the networks by existing techniques (see this article and this article). All of this is to be integrated in a set of methods and tools which the domain experts in our project can apply to (other) datasets. During the development of the theory, methods, and tools, you are expected to closely collaborate with domain experts in order to ensure relevance and validity of your approach.

The ideal candidate for this position:

• has a PhD in Complex Systems Science, Computational Science, Applied Mathematics, Applied Statistics, Statistical Physics, or related disciplines;
• has experience in high-level programming language(s) such as Python;
• has affinity towards and good knowledge of network science (graph theory). Preferably has experience in computational modelling of networks, network dynamics, and/or calculating various network topological features;
• enjoys interacting with domain experts from different disciplines and tackling an interdisciplinary problem by internalising and subsequently integrating qualitative knowledge into novel theory, computational models, and/or quantitative analyses;
• has experience in computational modelling and simulation techniques, such as Monte Carlo sampling;
• is trained in (multivariate) statistical analysis and/or information theory;
• has affinity towards contributing to a more holistic and multi-scale approach to managing human disease.

Our offer

A temporary contract for 12 months for 38 hours a week, preferably starting begin of January 2021, but this is flexible. After satisfactory evaluation the contract will be extended with 24 months.

The salary, depending on relevant experience before the beginning of the employment contract, will be €2,790 to €4,402 (scale 10) gross per month, based on a full-time contract of 38 hours a week. This is exclusive 8% holiday allowance and 8.3% end-of-year bonus. The Collective Labour Agreement of Dutch Universities is applicable.

Are you curious about our extensive package of secondary employment benefits like our excellent opportunities for study and development? Then find out more about working at the Faculty of Science.

University of Amsterdam

With over 5,000 employees, 30,000 students and a budget of more than 600 million euros, the University of Amsterdam (UvA) is an intellectual hub within the Netherlands. Teaching and research at the UvA are conducted within seven faculties: Humanities, Social and Behavioural Sciences, Economics and Business, Law, Science, Medicine and Dentistry. Housed on four city campuses in or near the heart of Amsterdam, where disciplines come together and interact, the faculties have close links with thousands of researchers and hundreds of institutions at home and abroad.  

The UvA’s students and employees are independent thinkers, competent rebels who dare to question dogmas and aren’t satisfied with easy answers and standard solutions. To work at the UvA is to work in an independent, creative, innovative and international climate characterised by an open atmosphere and a genuine engagement with the city of Amsterdam and society.

Faculty of Science - Informatics Institute

The Faculty of Science has a student body of around 7,000, as well as 1,600 members of staff working in education, research or support services. Researchers and students at the Faculty of Science are fascinated by every aspect of how the world works, be it elementary particles, the birth of the universe or the functioning of the brain.

The mission of the Informatics Institute is to perform curiosity-driven and use-inspired fundamental research in Computer Science. The main research themes are Artificial Intelligence, Computational Science and Systems and Network Engineering. Our research involves complex information systems at large, with a focus on collaborative, data driven, computational and intelligent systems, all with a strong interactive component.

The Computational Science Lab (CSL) at the Informatics Institute tries to understand how information is processed in natural settings through the study of a large variety of dynamic multi-scale complex systems. The University of Amsterdam (UvA) is consistently ranked among the top 70 in the QS Global World Rankings; the embedding informatics institute is even ranked 45th. The project is part of the 'TO_AITION' EU Horizon 2020 project. In terms of embedding, you will regularly visit the Institute for Advanced Study (IAS) of the UvA and become connected through nation-wide societies such as the Dutch NetSci chapter, the Netherlands Platform of Complex Systems, and the Dutch Institute of Emergent Phenomena. You will join an interdisciplinary team, consisting of researchers from the Computational Science Lab (CSL), the Clinical Psychology program group in the Psychology Research Institute, and collaborators over various countries in the corresponding EU Horizon 2020 project.