TranSYS ESR Recruitment

Still a few positions left in the EU Horizon 2020 Marie Skłodowska-Curie Project TranSYS

TranSYS, coordinated by K. Van Steen (KU Leuven), will recruit 15 ESRs (Early Stage Researchers) to highly skilled jobs in the new area of Systems Health developing tools and approaches to exploit large and complex datasets, to advance Precision (Personalised) Medicine in several disease areas. The training programme and experience of different international research environments cuts across traditional data and life sciences silos. The emphasis on translational research will support new collaborations between academics and the pharma and health analytics sectors. Our ESR projects will advance the state of the art on biomarker discovery, improve understanding of disease-specific molecular mechanism and target identification for optimal diagnostics, disease risk and treatment management, refine data generation and their management (including warehousing, disease specific and standardised approaches for data processing, visualisation and model development) leading to improved clinical study design, clinical sampling and more targeted therapeutics. This ETN (European Training Network) will internationalise participants, and leverage EC (European Commission) and industry sponsorship, to structure and expand the unique training programme and advance emerging research areas, combining wet-lab, clinical and Big Data resources with computational and modelling know-how.

To achieve a paradigm shift in research training this ETN brings together international leaders in Preclinical Science & Molecular Medicine, Systems Analytics, and Targeted Therapeutics, from academia and industry. These experts are ideally positioned to develop the proposed training programme and deliver a highly-trained workforce of next generation scientists, with the right mind-set, knowledge and skills, at the interface of Translational and Systems Medicine. The TranSYS training programme is designed to addresses a critical skills gaps that is currently a bottleneck to advancing Precision Medicine.

Call for applicants: rolling recruitment [extension 2nd call] [1st call closed]:

Key dates

Rolling recruitment:

  • 21-12-2019: Candidates are evaluated on a rolling bases
  • Top candidates per ESR topic will be contacted for an interview. Positions remain open until filled. Target starting date for ESR contracts: As soon as possible, in mutual agreement (estimated: February 2020)

Second call:

  • 14-11-2019: Start date for on-line application [2nd call]
  • 13-12-2019: Deadline for on-line application
  • 18-11-2019 – 24-01-2020: Applicants evaluation / selected candidates interviewed by TranSYS partners.
  • 27-01-2020: All candidates notified about the outcome of the selection process
  • Target starting date for ESR contracts: As soon as possible, in mutual agreement (estimated: February 2020)

First call:

  • 15-07-2019: Start date for on-line application [1st call]
  • 14-11-2019: Applicants evaluated / selected applicants interviewed by TranSYS partners.
  • Target starting date for ESR contracts: As soon as possible, in mutual agreement (estimated: February 2020)

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Key background info


TranSYS wishes to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background. Recruitment targets ESR backgrounds in:
1) Lifesciences;
2) Engineering sciences and
3) Maths and Computational Modelling.

In total 15 early-stage researchers will be recruited that will work at the 13 beneficiaries all across Europe.

We expect that applicants hold a university degree that qualifies them for doctoral studies at their recruiting organization. Solid written and oral communication skills in English are prerequisites of any successful application (typically IELTS min. 7, TOEFL internet-based min. 90 or similar level as proven by other tests). Every applicant can apply for up to three ESR positions (first, second, third choice)

Career Stage

Early Stage Researcher (ESR) or 0-4 yrs (Post Graduate)

Benefits and salary

The successful candidates will receive an attractive salary in accordance with the MSCA regulations for Early Stage Researchers. The exact (net) salary will be confirmed upon appointment and is dependent on local tax regulations and on the country correction factor (to allow for the difference in cost of living in different EU Member States). The salary includes a living allowance, a mobility allowance and a family allowance (if married). The guaranteed PhD funding is for 36 months (i.e. EC funding, additional funding is possible, depending on the local Supervisor, and in accordance with the regular PhD time in the country of origin). In addition to their individual scientific projects, all fellows will benefit from further continuing education, which includes internships and secondments, training in complementary skills via participation at local and network-based events, active participation in workshops and conferences, supervision by recognized experts and access to (beyond) state-of-the-art research and pilot-scale infrastructure.

On-line Recruitment Procedure

All applications proceed through the on-line recruitment portal on the website. Candidates apply electronically for one to maximum three positions and indicate their preference. Candidates provide all requested information including a detailed CV (Europass format obligatory) and a motivation letter describing your motivation to apply, your research career goals, skills and experience. During the registration, applicants will need to prove that they are eligible (cf. ESR definition, mobility criteria, and English language proficiency). The deadline for the on-line registration is 13 December 2019.


Applicants need to fully respect three eligibility criteria (to demonstrated in the Europass cv):

Early-stage researchers (ESR) are those who are, at the time of recruitment by the host, in the first four years (full-time equivalent) of their research careers. This is measured from the date when they obtained the degree which formally entitles them to embark on a doctorate, either in the country in which the degree was obtained or in the country in which the research training is provided, irrespective of whether or not a doctorate was envisaged.

Conditions of international mobility of researchers:

Researchers are required to undertake trans-national mobility (i.e. move from one country to another) when taking up the appointment. At the time of selection by the host organisation, researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of their host organisation for more than 12 months in the 3 years immediately prior to their recruitment. Short stays, such as holidays, are not taken into account.

English language: Network fellows (ESRs) must demonstrate that their ability to understand and express themselves in both written and spoken English is sufficiently high for them to derive the full benefit from the network training.

The available PhD positions


ESR1: Development of individual-specific molecular networks

ESR1: Development of individual-specific molecular networks

Host: KU LEUVEN (Leuven University) (BELGIUM)

PhD awarding institution: KU LEUVEN (Leuven University)

Lead Supervisor: K Van Steen


Objectives: Describing a system implies describing its behavior and important control mechanisms that regulate this behavior. Crucial in this process are interactions, which may occur at different levels or scales, and thus network theory and network visualization are increasingly being used to understand biological mechanisms operating in human systems. However, an individual, especially when in poor health, is likely to deviate from the “norm” in human systems. In this project, we wish to develop omics data integrative gene-based networks to enhance PM. Such a network would enable the identification of gene modules that are subject-specific (in network nodes/edges) and comprise multi-layer cellular information. It goes beyond existing work in that genes are considered to be complex multi-omics systems, and that statistical significance is assessed for individual-specific nodes/edges (in contrast to f.i. Menche et al. 2017 and Kuijjer et al. 2018). We aim to achieve our goal by building upon the aforementioned references and our work on gene representations using diffusion kernels and network theory (Fouladi et al. 2018). Personalized gene omics-integrative signatures will primarily be derived by combining genome, transcriptome and epigenome data for complex diseases with an inflammatory component.

ESR3: GDPR regulation in translational medicine

ESR3: GDPR regulation in translational medicine



Lead Supervisor: P van der Spek


Objectives: First results on integrated omics profiling of melanoma patients, in particular primary and metastasized skin cancer patients, are promising and seem to generate interesting biomarkers with therapeutic potential. The main aim of this project is to develop a patient stratification strategy based on multi-omics data bases and a tool that enables a reliable classification of clinically relevant disease subtypes via advanced pattern recognition that can be readily translated to clinic (e.g., dermatology). Day-to-day problems in the clinic focusing on getting the right drug into the right melanoma patient are taken as case study. To achieve our goals, we will expand on previous work performed by the department of bioinformatics, pathology, clinical genetics and dermatology.

ESR6: Dissecting cellular heterogeneity of Parkinson’s disease (PD) related iPS cells during aging by integrated single cell transcriptomics and imaging analysis to identify disease modifiers

ESR6: Dissecting cellular heterogeneity of Parkinson’s disease (PD) related iPS cells during aging by integrated single cell transcriptomics and imaging analysis to identify disease modifiers


PhD awarding institution: UNIVERSITE DU LUXEMBOURG

Lead Supervisor: A Skupin


Objectives: Recently established patient derived iPS cell approaches typically neglect the effect of aging by working with freshly differentiated cells. The proposed project will address this challenge using our PD based iPS cell collection and 1) Characterizing cellular heterogeneity during differentiation and aging of personalized iPS cells by integrating microscopy with single cell RNAseq analysis; 2) Developing a bioinformatics pipeline to identify potential disease modifiers based on network analysis and imaging based validation; 3) Integrating the obtained data into a dynamic model of cell differentiation and aging in neurodegeneration.

ESR9: Patient-centric data integration framework for highly dimensional data

ESR9: Patient-centric data integration framework for highly dimensional data


PhD awarding institution: UNIVERSITAT DE BARCELONA

Lead Supervisor: N Pržulj


Objectives: PM proposes to individualize the practice of medicine based on patients’ genetic backgrounds, their biomarker characteristics and other omics datasets including exposure. ESR9 will build upon our previous work on network science, data integration and PM to propose a patient-centric data integration framework that enables all of the following: (1) improved patient stratification (allowing for predicting disease outcomes with more confidence), (2) uncovering molecular bases of diseases (molecular mechanisms, disease genes, biomarkers), and (3) personalized treatment predictions (drug repurposing). In practice, the mutational data will be mapped onto molecular networks and graphlet-based approaches will be utilized for mining for medically relevant signals. All data will be integrated using non-negative matrix factorization based approaches (Zitnik et al 2013; Gligorijevic et al. 2016) into a unified framework from which additional knowledge will be mined. Unlike existing approaches that only represent and integrate biological data as networks, we will thus also consider alternative data representation, such as hyper-networks and simplicial complexes that can capture the multi-scale organization of the data.


ESR12: Multi-omics analysis to delineate drug-response pathways

ESR12: Multi-omics analysis to delineate drug-response pathways



Lead Supervisor: C Wijmenga


Objectives: Response to drugs is highly heterogeneous. On average medication works in only 25% of cases, and efficacy varies between patients. ESR 12 will develop stratification rules for individuals, based on genetics. For this to be effective, deep understanding of the role of drug-metabolizing SNPs in drug response pathways, and interactions with pertinent biological mechanisms and disease pathways is necessary. 1) To expand on this by investigating the molecular pathways in predicted responders and non-responders using multi-omics data (genomics, RNA-seq, methylation, metabolomics, microbiome). 2) To exploit a population-based cohort (cross-sectional) of ~1500 individuals (LifeLines-Deep – Tigchelaar et al. 2015) for which the multi-omics data have been generated already and from which 1000s of phenotypes are known, using PheWas analysis. 3) Stratify individuals based on existing knowledge about the impact of genetic variation on drug response and investigate the downstream biological consequences in a wealth of molecular parameters. At the same time, the drug metabolizing SNPs will be assessed for any impact on other clinical phenotypes.

ESR15: Developing and demonstrating data mining and A.I. tools to better understand patient heterogeneity and assist patient stratification

ESR15: Developing and demonstrating data mining and A.I. tools to better understand patient heterogeneity and assist patient stratification


PhD awarding institution: UNIVERZA V LJUBLANI

Lead Supervisor: V Martins dos Santos


Objectives: Instead of creating new data, it is often easier, more cost-effective and in many cases even more productive to make use of the data that is already present and that just waits to be collected, harmonized and analyzed from a different viewpoint. Many public databases, e.g. dealing with omics data or clinical studies, provide so called Application Programming Interfaces (APIs) for fast, easy and most importantly automated access of their data. The objectives are to use this “hidden” potential in already created data by 1) structuring the database for related samples; 2) designing and developing a data mining tool that accesses, collects and harmonizes data via those APIs and makes it easily usable for further downstream interpretation/analysis; 3) implementing an artificial intelligence algorithm that would classify automatically a specific sample or that would detect a potential misclassification; 4) undertaking proof of concept case studies using Decipher CNV data of patients suffering from developmental neurological malformations that might hit/overlap with the Encode data and also using metabolic liver pathologies. Interpretation focuses on patient similarity, heterogeneity aiming on data re-use for personalized medicine. This will integrate the extent the collected data from various open access data sources aiming on contributing to a better understanding of patient similarity and or heterogeneity for personalized medicine.





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Full recruitment procedure available here: Recruitment Document

This project is to receive funding from the European Union’s EU Framework Programme for Research and Innovation Horizon 2020, pending the formal completion of the Grant Agreement (No 860895) procedure.