Marie Skłodowska-Curie Actions
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PhD stundent: Computer assisted morphometry of pathological changes in renal biopsies from patients with AAV

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    TissueGnostics GmbH
    Medical sciencesMedicine
    First Stage Researcher (R1)
    26/02/2019 17:00 - Europe/Brussels
    Austria › Vienna
    H2020 / Marie Skłodowska-Curie Actions


Are you a rising star in the field of image analysis / machine learning and keen to apply this to histological data, in the first four years of your research career and based outside Austria? Do you want to further your career and attain a PhD in one of Austria’s most innovative Life Science company in conjunction with the Medical University of Vienna, Department of Pathology?

To meet the requirements of the Marie Skłodowska-Curie Innovative Training Network, you will be an early stage researcher within the first four years of your research career, have not yet been awarded a doctoral degree (PhD), and have not lived or carried out your main activity (work/study) in Austria for more than 12 months in the three years immediately before the recruitment date.

As well as previous research experience, you will have a good honours Master’s Degree in computer science or a related discipline.

The post is for 1 early stage researcher (ESR) who will undertake a three year PhD studentship as part of the H2020-MSCA-ITN-2018 HELICAL (Co-ordinator: Professor Mark Little, Trinity College Dublin, TCD). HELICAL is an EU funded Marie Curie Innovative Training Network (ITN) with 17 Academic Partners (TCD (IRL); MedUni Vienna (A); University of Glasgow, Farr Institute, University of Leeds, Leeds Institute for Data Analytics (UK); Universite Paris Diderot (F); Kungliga Tekniska Hoegskolan, Uppsala Universitet (S); Consorci Institut d´Investigations Biomediques, Consejo Superior De Investigaciones Cientificas, Instituto de Salud Global de Barcelona, Instituto de Investigaciones Marques de Valdecilla, Universitat de Barcelona, Universitat Autónoma de Barcelona (E); Charles University (CZ);  Ghent University (B)) and nine Non-Academic Partners (Tissuegnostics (A); IBM Zurich (CH), patientMpower (IRL); Anaxomics Biotech (E); Firalis (F); European Institute for Innovation in Health Data (B); RITA European Reference Network, Laser Analytica, Eagle Genomics (UK)). The HELICAL training program focuses on three complementary areas: application of informatics to such datasets to gain new biological insights; translation of these into practical clinical outputs and management of ethical constraints imposed on such studies.


The appointee will be trained in advanced image cytometry, statistical genetics and systems biology applied to giant cell arteritis pathogenesis. General training will include enhancement of their awareness of FAIR and GDPR data principles. The HELICAL ITN is highly integrated and so the appointee will also have the opportunity to acquire additional skills through regular meetings, workshops and seminars, and through secondments to other partners in the HELICAL network.

The present post is to be based at TissueGnostics GmbH Austria in conjunction with the Department of Pathology at Medical University Vienna and supervised by Professors Renate Kain and co-supervised by Dr Rupert Ecker (TG: Vienna, Austria) with planned secondments at Medical University Vienna.

Rationale: Application of machine learning to kidney biopsy tissue morphometry, with correlation to clinical outcome parameters, can improve diagnostic and prognostic fidelity in renal AAV.

Objectives: Machine learning: standardised automated identification of defined changes (descriptors) in renal biopsies. Validation of machine learning: comparison of “computer” recognised and manually determined changes. First clinical outcome study: defined descriptors suited to automated analysis will be correlated to clinical outcome in a small set of patients from the MUW cohort. Clinical validation study: additional patient biopsies from RKD biobank will be included to validate automated descriptor evaluation and their suitability to predict outcome using variable clinical data sets.

Expected Results: Development of algorithms that allow automated analysis of predictive changes in renal biopsies in AAV.

HELICAL is funded under the H2020-MSCA-ITN-2018 designed to promote movement of researchers in Europe and so is open to researchers from any country in the world provided they have not carried out their main activity (work, studies, etc.) in Austria for more than 12 months in the 3 years immediately before the recruitment date. HELICAL pursues a policy of equal opportunities on matters of gender and disability and will seek to recruit an equal proportion of male and female applicants and will provide employment opportunities for candidates with disabilities. Where applications of equal quality are received, preference will be given to female candidates as part of a strategy designed to recruit equal numbers of men and women to the HELICAL posts. Employment procedures and contracts will conform to the European Charter for Researchers / Code of Conduct for the Recruitment of Researchers.



The per annum Marie Skłodowska-Curie Early Stage Researcher living and mobility allowance (plus family allowance if applicable) is in line with Marie Skłodowska-Curie Innovative Training Network requirements. This amount will be subject to tax and employee’s National Insurance deductions, and will be paid in Euro (€).



More Information


Our other research

For more information about the supervisors in Vienna, please visit their personal webpages



A diverse workforce

The Medical University Vienna as well as TissueGnostics are committed to providing equal opportunities for all and offer a range of family friendly policies. We are proud to be an inclusive Faculty that values all staff, and are happy to consider job share applications and requests for flexible working arrangements from our employees.

Eligibility criteria

The post is a PhD studentship to be appointed to TissueGnostics GmbH, Vienna, Austria, as part of the “HEalth data LInkage for ClinicAL benefit (HELICAL)“ H2020-MSCA-ITN-2018 Innovative Training Network.

European researchers have made leading contributions to the large genomic, transcriptomic and clinical datasets from patients with chronic vascular diseases. Advances in information science provide unprecedented opportunities for using these datasets to elucidate the complex biology of these disorders, its influence by environmental triggers, and to personalise their management. Currently, exploitation of these opportunities is limited by a shortage of researchers with the required informatics skills and knowledge of requisite data protection principles. HELICAL addresses this unmet need by developing a trans-sectoral and interdisciplinary training programme that provides 15 early stage researchers with training in analysis of large datasets, using autoimmune vasculitis as a paradigm, as comprehensive biological and clinical datasets are already available. The programme will be delivered through a multidisciplinary, trans-sectoral partnership of Academic and Industry researchers with expertise in basic biomedical research, epidemiology, statistics, machine learning, health data governance and ethics. Therefore, HELICAL exploits recent advances in data science to link research datasets with longitudinal healthcare records, based on the robust ethical foundation required for linkage studies using near-patient data, to address key experimental questions.

Selection process

Candidates with disabilities

Information for candidates with disabilities, impairments or health conditions, including requesting alternative formats, can be found here:


Criminal record information

A criminal record check is not required for this position. However, all applicants will be required to declare if they have any ‘unspent’ criminal offences, including those pending.

Any offer of appointment will be in accordance with our Criminal Records policy.

Additional comments

Working in Vienna

The rating agency Mercer has elected Vienna as “City with highest living quality in the world” for the 8th year in line


Required Research Experiences

    Computer science
    1 - 4

Offer Requirements

    Biological sciences: Master Degree or equivalent
    Computer science: Master Degree or equivalent
    Medical sciences: Master Degree or equivalent
    ENGLISH: Excellent


As an Early Stage Researcher you will have:

  • a good honours Master’s Degree (minimum upper second or equivalent) in statistics or a related discipline;
  • The ability to meet all eligibility requirements for appointment in Austria as an Early Stage Researcher funded by the Marie Skłodowska-Curie Innovative Training Network:
    • You must be within the first four years (full-time equivalent) of your research career, and have not yet been awarded a doctoral degree (e.g. PhD), at the time of recruitment to this role;
    • You must not have resided or carried out your main activity (such as work or study) in Austria for more than 12 months during the three years prior to your recruitment to this role;
  • The ability to meet the Medical University Vienna’s eligibility requirements to enrol on a PhD degree;
  • English language requirements if English is not your first language; British Council IELTS – Overall score of 7.0 with no element less than 6.5 or TOEFL (iBT) – Overall score of 100 with the reading element no less than 22, speaking element no less than 24, listening element no less than 22 and the writing element no less than 23. In order to be deemed valid by the UK Border agency, the score must be less than two years old by your start date at Leeds.
  • Flexibility to travel throughout the EU;
  • Experience of undertaking academic research; Master’s degree is a prerequisite, experience in statistics, bioinformatics or computational biology would be advantageous;
  • Good IT skills;
  • Excellent analytical and problem-solving skills with good attention to detail;
  • Familiarity with statistical software (e.g. R, Stata);
  • Good interpersonal and communication skills, both written and verbal, and the ability to communicate effectively with a wide range of stakeholders;
  • Good time management and planning skills, with the ability to meet tight deadlines and manage competing demands effectively;
  • A proven ability to work well both independently and as part of a team;
  • A strong commitment to your own continuous professional development.
  • Good computer programming skills

Specific Requirements

As an Early Stage Researcher your main duties will include:

  • Contributing to the HELICAL Innovative Training Network (ITN) under the supervision of Professor Renate Kain at Medical University of Vienna and co-supervised by Dr. Rupert Ecker of TissueGnostics GmbH Austria;
  • Undertaking ongoing research at doctoral degree level as outlined in the ESR12 project description above;
  • Participating in HELICAL ITN activities to ensure a successful programme of investigation, including attending group meetings and seminars, training courses and site visits; as well as collaborating with academic and industrial partners;
  • Contributing to the dissemination of research results in leading peer-reviewed journals and through presentation at meetings and conferences, with guidance as necessary;
  • Ensuring good progress of your work and keeping up-to-date records;
  • Providing support and advice to other members of the ITN;
  • Working both independently and as part of a larger team of researchers and stakeholders;
  • Continually updating your knowledge, understanding and skills in the research field in which you work.


These duties provide a framework for the role and should not be regarded as a definitive list. Other reasonable duties may be required consistent with the grade of the post.

Work location(s)
1 position(s) available at
TissueGnostics GmbH
Taborstrasse 10

EURAXESS offer ID: 380783


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