HYBRID: 15 Early Stage Researcher (ESR) positions; fully-funded 1904 views

HYBRID project seek to provide essential information to personalized medicine concepts that involve non-invasive imaging procedures. Personalized medicine is the practice of using selected and measured characteristics to guide decisions on prevention, diagnosis and treatment of disease for patient groups and individual patients, and is representative of a paradigm shift in patient management.

HYBRID2020 Consortium offers 15 early stage researcher (ESR) positions.

Duration: 3-year full time appointments

Fellowship value: fully funded

About the programme:

• Each ESR will be assigned an individual research project that will lead to a PhD (ESRs will be enrolled in the local PhD programs).
• All ESRs will participate in the interdisciplinary HYBID training program, which aims to support the ESRs to tackle the challenges of imaging science of tomorrow.

Participating organizations:

• Medical University of Vienna (MUW)
• University of Leuven (KU Leuven)
• Philips Electronics Nederland B.V.
• The French Alternative Energies and Atomic Energy Commission (CEA)
• University Medical Centre Groningen (UMCG)
• King’s College London (KCL)
• Werner Siemens Imaging Center, Tübingen, Germany
• ABX-CRO Advanced Pharmaceutical Services m.b.H.
• Technical University of Munich
• Siemens Healthcare GmbH
• University of Copenhagen

Eligibility:

• Mobility Rule: applicant must not have resided in the country where the research training activities take place for more than a year in the 3 years immediately prior to the recruitment date (and not have carried out their main activity (work, studies, etc.) in that country)
• Early Stage Researcher: applicant must be (at the date of recruitment) an ‘early stage researcher’ (in the first four years (full-time equivalent) of his/her research career and not have a doctoral degree)

Projects:

ESR1 – Standardized quality assurance protocols in multi-parametric imaging

ESR2 – Multi-modality imaging for treatment planning of selective internal radionuclide therapy (SIRT)

ESR3 – Fully-quantitative PET for improved diagnosis and therapy response monitoring in breast cancer

ESR4 – Whole-body parametric PET/MR imaging for improved therapy response assessment in metastatic diseases

ESR5 – Multi-Parametric Pharmacokinetic Approaches for Improved brain PET quantification

ESR6 – Hybrid PET/MRI for improved tumour grading and detection of recurrent/residual disease in Neuro-Oncology

ESR7 – Simultaneous PET-MRI to enhance quantification and change-detection in tumour assessment

ESR8 – Machine Learning in Digital Histopathology

ESR9 – Tumour ID cards for multi-scale characterization of tumour heterogeneity

ESR10 – Predictive therapeutic dosimetry and treatment evaluation using Deep Learning Neural Network

ESR11 – Developing a clinical workflow for improved tissue characterization based on MPI in oncology

ESR12 – Improving staging through machine learning based on multiparametric imaging: a collaborative platform

ESR13 – Multiparametric Imaging in Radiotherapy Planning

ESR14 – Ultrasound guided intervention based on hybrid image information

ESR15 – Quantitative multi-modality cardiac imaging in diagnosis and therapy monitoring

How to apply:

• Apply online