The post is one PhD studentship to be appointed to the Department of Pathology, Medical University of Vienna as part of the “HEalth data LInkage for ClinicAL benefit (HELICAL)“ H2020-MSCA-ITN-2018 Innovative Training Networks.
They aim to train a new generation of creative, entrepreneurial and innovative early stage researchers, able to face current and future challenges and to convert knowledge and ideas into products and services for clinical benefit. Researchers shall be equipped with the right combination of research–related and transferable competences. Training should provide enhanced career perspectives in both the academic and non-academic sectors through international, interdisciplinary and intersectoral mobility combined with an innovation-oriented mind-set.'
The post is for an 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 Aberdeen, 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-Newcastle University, Laser Analytica, Eagle Genomics (UK)). It will provide a trans-sectoral and interdisciplinary training programme with state of the art training in analysis of large datasets from individuals with chronic inflammatory disease, using autoimmune vasculitis as a paradigm. HELICAL key complementary areas: application of informatics to such datasets to gain new biological insights, translation of biological into practical clinical outputs, and identification of novel ethical constraints and development of strategies to manage them.
The appointee will be trained in advanced data science, machine learning, systems biology and clinical applications and to enhance 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.
Required Research Experiences
Medical sciences › Medicine
YEARS OF RESEARCH EXPERIENCE
1 - 4
REQUIRED EDUCATION LEVEL
Medical sciences: Master Degree or equivalent
Experience of undertaking academic research; experience in statistics, bioinformatics or computational biology would be an advantage
Good IT skills
Excellent analytical and problem-solving skills with good attention to detail
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
Ability to perform practical experimental measurements
Ability to interpret results and perform analysis on experimental data
Ability to write scientific reports and papers using clear and concise English
HEalth data LInkage for ClinicAL benefit HELICAL
Ability to communicate research results through scientific presentations
Ability to develop creative approaches to problem solving
Ability to analyse and solve problems with an appreciation of longer-term implications
Ability to direct own day-to-day work
As the project may involve patient contact and recruitment, medical training and some command of the German language are beneficial, but not mandatory.
Analysis of data sets from proteomics and transcriptomics
Cell culture and generation of extracellular vesicles
Web site for additional job details
Where to send your application:
Medical University of Vienna