Skip to main content
EURAXESS

The MSCA SHARE-CTD network offers 11 full time PhD projects in 6 countries for Masters in data science / biostatistics / medical informatics / medicine / clinical trials / (clinical) epidemiology

24 Aug 2023

Job Information

Organisation/Company
Ludwig Maximilian University of Munich
Department
Institute for Medical Information Processing, Biometry, and Epidemiology
Research Field
Medical sciences » Epidemiology
Mathematics » Statistics
Computer science » Other
Researcher Profile
First Stage Researcher (R1)
Country
Germany
Application Deadline
Type of Contract
Temporary
Job Status
Full-time
Offer Starting Date
Is the job funded through the EU Research Framework Programme?
H2020 / Marie Skłodowska-Curie Actions
Marie Curie Grant Agreement Number
101120360
Is the Job related to staff position within a Research Infrastructure?
No

Offer Description

Sharing and re-using clinical trial data to maximise impact (SHARE-CTD)

Clinical trial results are the source of foundational evidence for contemporary medical decision making. This evidence is widely used by regulatory bodies, health technology assessment agencies, and is considered the gold standard for assessing treatment effects. The value and trustworthiness of medical research may be enhanced by sharing of patient-level clinical trial data together with the code on which analyses are based as well as other materials such as the protocol, case report form, and data dictionary. Keeping this background in mind, clinical trial data sharing (CTDS) offers unique opportunities for external re-analysis, which enables conclusions to be re-examined, verified or, occasionally, corrected, thereby building trust. CTDS also allows individual participant data (IPD) meta-analysis and other strategies that build upon previous data and code, such as secondary analyses and methodological work. CTDS should accelerate discovery, reduce false discovery rates, and potentially discourage misconduct and research waste, as well as allowing more value to be drawn from the original research investment. CTDS honours the generosity of clinical trial participants, because it maximises the utility of the data they provide, and is widely viewed as a positive feature by stakeholders involved in clinical trials, including trial participants.

In this European PhD Curriculum, students will leverage diverse fields, including biostatistics, computer science, machine learning, and meta-research to establish robust practices and methodologies for clinical trial data sharing. They will work on a multi-disciplinary area, enhancing the utility of shared clinical trial data while safeguarding its integrity. Through their individual research efforts, they will contribute to expanding our understanding of data sharing and re-use, tackling issues from data anonymisation to outcome reporting bias. Furthermore, they will investigate the real-world impact of clinical trial data sharing on healthcare and medical practices. The overarching goal is to advance scientific knowledge in order to shape policy and guidelines, thereby revolutionising the way we share and use data in clinical trials.

Their research will be embedded and supported by a training programme based on theory, practice and experience. Doctoral candidates who complete the programme will know how to perform research to advance best practices for CTDS, and how to perform data sharing with a high level of professionalism. They will be able to address the following important issues: 1) enhancing public access to clinical study information, 2) reaffirming commitments to publish clinical trial results, 3) sharing results with patients who participate in clinical trials, 4) certifying procedures for sharing clinical trial information, and 5) enhancing data sharing with clinical researchers.

Through the involvement of a large international network of partners, SHARE-CTD will allow a profound interaction with a wide range of experts as well as problem-based interactive methods such as datathons that promote transparency, honesty and collaboration. It will prepare the candidates for a wide range of positions in academic and non-academic fields.

Projects provided by SHARE-CTD

  1. Role of CTDS for validation of prognostic and predictive models for MS patients – Dr. Ulrich Mansmann, LMU München, Germany
  2. Impact of clinical trial data sharing – Dr. Florian Naudet, University of Rennes, France
  3. Innovative approaches to trial data anonymisation and its role for CTDS – Dr. Fabian Prasser, Charité, BIH, Germany
  4. Automated screening tools for identifying data sharing, data-re-use and common reporting problems in clinical trials – Dr. Tracey Weissgerber, Charité, BIH, Germany
  5. Methodology for FAIRification, Data Enrichment and Data Sharing – Dr. Ulrich Sax, University Medical Center Göttingen, Germany
  6. Added value of meta-analyses of shared individual patient data (IPD) in mental health – Dr. Ioana-Alina Cristea, University of Padova, Italy
  7. Towards Understanding and accepting data sharing within patients – Dr. Evelyne Decullier, Hospices Civils de Lyon, France
  8. Methodology for cross-design synthesis – Dr. Valentijn de Jong, University Medical Center Utrecht, The Netherlands
  9. Using shared historic data to augment prospective clinical trials – Dr. Martin Posch, Medical University Vienna, Austria
  10. Evaluating outcome reporting bias in clinical trials – Dr. Leonhard Held, University of Zürich, Switzerland
  11. Impact of clinical trial data sharing for pivotal trials in oncology – Dr. Clara Locher, University of Rennes, France.

The application process will follow the EU code of conduct (https://euraxess.ec.europa.eu/jobs/charter/code)

Requirements

Research Field
Medical sciences » Epidemiology
Education Level
Master Degree or equivalent
Research Field
Mathematics » Statistics
Education Level
Master Degree or equivalent
Research Field
Computer science » Other
Education Level
Master Degree or equivalent
Skills/Qualifications

The candidates should have a strong background in the fields mentioned above. The candidates should not have a PhD. Depending on the project type, knowledge of data analysis, (bio)statistics, machine learning and associated programming skills or medicine, clinical trial regulations, epidemiology, and meta-research are essential.

The candidates should be able to work independently, take initiative, adopt critical judgment and demonstrate ability to work in team. The candidates should be motivated to work with and listen to experts with a clinical, biostatistical, informatic, meta-research, or regulatory background. The project will include several network wide educational events and secondments, for which travel, communication and social skills are required.

Proficiency in written and spoken English is crucial.

The candidates can be of any nationality, but must not have resided or carried out his/her main activity in the country of the recruiting beneficiary for more than 12 months in the 3 years immediately prior to his/her recruitment (mobility rule of the EU).

The selected candidates are expected to write a doctoral thesis on their research after 3 years (when relevant, a 4th year of research will be funded by the host institution).

Perspectives for selected candidates:

  • Integration in an international network of specialists in clinical trial methodology, medical informatics, data science, Meta-Research.
  • A full time PhD position in one of the 9 world-renowned research institutions and in the multidisciplinary environment of the SHARE-CTD network, under supervision of and in close collaboration with experts from a wide variety of domains.
  • A thorough scientific education and training in all relevant competences to advance the field of data sharing, enabling the possibility to become a world-class researcher and expert in this field.
  • The possibility to actively participate in the network’s organisational structure and in international conferences and collaborations.

A predetermined living allowance (corrected according to the country coefficient of the country of employment), and mobility allowance, and when appropriate a family allowance, long-term leave allowance or special needs allowance integrally transferred to the researchers.

Specific Requirements

Research Field                                    Medical Informatics
Education Level                                   Master Degree or equivalent

Research Field                                    Computer Science
Education Level                                   Master Degree or equivalent

Research Field                                    Data science
Education Level                                   Master Degree or equivalent

Research Field                                    Biostatistics
Education Level                                   Master Degree or equivalent

Research Field                                    Medicine
Education Level                                   Master Degree or equivalent

Research Field                                    Clinical Trials
Education Level                                   Master Degree or equivalent

Research Field                                    (Clinical) Epidemiology
Education Level                                   Master Degree or equivalent

Research Field                                    Ethical, legal, societal issues in Medicine (ELSI)                                                     
Education Level                                   Master Degree or equivalent

or similar fields with expertise on master level.

Languages
ENGLISH
Level
Good
Research Field
Medical sciences » Epidemiology
Research Field
Mathematics » Statistics
Research Field
Computer science » Other

Additional Information

Selection process

For more information on the PIs, the project specific requirements, and the application process see our website: https://SHARE-CTD.eu or contact the network coordinator (Dr. Ulrich Mansmann, ulrich.mansmann@lmu.de).

The two-stage application procedure will be carried out in compliance with the Code of Conduct for Recruitment and the Charter for Researchers (https://euraxess.ec.europa.eu/jobs/charter-code-researchers).

  1. The first stage consists of sending your documents (CV and motivation letter, master degree, references, PDF of master thesis) and filling out the required information within the application portal of SHARE-CTD between November 15th 2023 at the earliest and January 31st 2024 at the latest. Please note that we will only evaluate fully completed application forms that are submitted via the application portal before the deadline (https://www.portal.graduatecenter.uni-muenchen.de/ocgc/share-ctd).
    You can choose up to three projects of interest.
  2. Second stage: Selected candidates from the first stage will be invited for interview, possibly remotely, with the network PIs.
Website for additional job details

Work Location(s)

Number of offers available
1
Company/Institute
IBE at Ludwig-Maximilian’s University Munich
Country
Germany
City
Munich
Postal Code
80539
Street
Geschwister-Scholl-Platz 1
Geofield
Number of offers available
2
Company/Institute
IRSET at University of Rennes
Country
France
City
Rennes
Postal Code
35000
Street
9 Av. du Professeur Léon Bernard
Geofield
Number of offers available
2
Company/Institute
BIH at Charité – Universitätsmedizin Berlin
Country
Germany
City
Berlin
Postal Code
10178
Street
Anna-Louisa-Karsch-Str. 2
Geofield
Number of offers available
1
Company/Institute
DMI at University Medical Centre Göttingen
Country
Germany
City
Göttingen
Postal Code
37075
Street
Robert-Koch-Straße 40
Geofield
Number of offers available
1
Company/Institute
DGP at University of Padova
Country
Italy
City
Padova
Postal Code
35122
Street
Via VIII Febbraio, 2
Geofield
Number of offers available
1
Company/Institute
CeDAS at Medical University Vienna
Country
Austria
City
Wien
Postal Code
1090
Street
Spitalgasse 23
Geofield
Number of offers available
1
Company/Institute
SREC at Hospices Civils de Lyon
Country
France
City
Lyon
Postal Code
69002
Street
3 Quai des Célestins
Geofield
Number of offers available
1
Company/Institute
JC at UMC Utrecht
Country
Netherlands
City
Utrecht
Postal Code
3584
Street
Heidelberglaan 100
Geofield
Number of offers available
1
Company/Institute
DB at University of Zurich
Country
Switzerland
City
Zurich
Postal Code
8050
Street
Binzmuehlestrasse 14
Geofield

Contact

State/Province
Bavaria
City
München
Website
Street
Marchioninistrasse 1515
Postal Code
81377
E-Mail
ulrich.mansmann@lmu.de