• 43007 Tarragona, Spain


OFFER DEADLINE : 30/09/2022 23:59:00 – Europe/Brussels                                            ORGANISATION/COMPANY : Université Bourgogne Franche Comté

Prof. F. MERIAUDEAU and AssocProf. A. LALANDE, established at the Université Bourgogne Franche Comté (UBFC), Dijon, France are interested in receiving Expressions of Interest of potential candidates for the Marie Sklodowska – Curie Doctorate Network (MSCA-DN-2021) call.

The overarching goal of our project is to study the correlation between WSIs (Whole Slide Images) and radiological images, such as PET and/or MRI to improve the radiological imaging screening. Thus, this project will perform the following tasks: (1) to analyse the intra-tumour heterogeneity in WSIs through a novel digital image analysis (DIA) techniques of multi-labelling in bright or in fluorescence field, (2) to extend this analysis to other tumour locations and various immunohistochemical markers, as well to further understand the tumour biology, and link these information to multiparametric MRI, 2D/3D mammograms and PET image analysis, (3) to perform a comprehensive analysis of tumour heterogeneity at the level of autoradiography and immunohistochemistry and to compare the obtained quantitative information with multiparametric radiological MRI and PET imaging, (4) to conduct the developed approaches on various tumour situations at the preclinical level first (high grade glioma, brain and lung metastases from BC). Once validated, this correlation will then be performed at the clinical level (glioma for instance), (5) the correlation between changes extracted from the MRI images and the genetic information collected from medical centres will be done, and (6) stereology estimates of 3D structure and genetic information will be also compared to 3D imaging (MRI).

For BosomShield, we are looking for a doctorate candidate will have the following responsibilities:
  • She/he will collaborate with diverse teams of engineering and medical researchers within BosomShield to create novel diagnostic tools for breast cancer, based on recent techniques in deep learning.
  • She/he will design and develop cutting edge methods based on machine learning, such as generative adversarial networks (GAN), spherical convolutional neural networks, or normal appearance autoencoders.
  • She/he will exploit the possibility of applying explainable AI and uncertainty quantification methods.

We are looking for talented and innovative self-motivated young scientists, strongly committed to high quality frontier and multi-disciplinary research and able to add new insights to the existing Université Bourgogne Franche Comté core expertise. Université Bourgogne Franche Comté as Hosting Institution located at Scientific Campus of Dijon, France has all the technical and scientific facilities for carry out this project.

The PhD students will be working in the IFTIM research group with the following persons:

whom are all expert in medical imaging and medical image analysis.

The objectives of IFTIM team are focused on two core fields in clinical imaging: deployment of new imaging markers for preclinical and then clinical aspects combined with the development of new applications. The second field is processing and analysis of medical images. This multidisciplinarity is achieved thanks to hospitalo-university researchers involved in applied research in medical imaging, biologists and physicists involved both in basic and applied research in medical imaging and finally computer scientists with expertise in processing and analysis of medical images. The team benefits from a promising environment for setting up research projects, in particular with the two public health institutions in Dijon metropole (University Hospital of Dijon and anti-cancer center (CGFL)) hosting both a comprehensive imaging unit and a preclinic imaging platform unique in France.

Benefit per month:
Gross salary: 2.814€,
+ Mobility grant: 426€
+family allowance : 355€

At the deadline for the submission of the proposals:
  • Early Stage Researcher:
    • Knowledge of deep learning concepts and experience with deep learning environments (e.g. TensorFlow and PyTorch).
    • Excellent practical software engineering ability, in particularly in Python.
    • Knowledge of medical image analysis and experience of working with image data.
    • A master of science degree or equivalent is required.
    • Collaborative spirit.
  • Nationality: Any.
  • Mobility: The researcher must not have resided or carried out his/her main activity (work, studies, etc.) in the country of the host organization for more than 12 months in the 3 years immediately prior to the deadline for submission of proposals (a relaxed rule for Career restarting and Reintegration).
  • Must be fluent in English (both written and spoken).

Researchers willing to apply should check that they fulfil the eligibility criteria and then send an expression of interest, consisting of:
  • Scanned copy of identity card, resident's card or passport currently in force.
  • Curriculum Vitae (Any research career gaps and/or unconventional paths should be clearly explained so that this can be fairly assessed by the evaluators; if you are a forcibly displaced researcher, please explain your situation in the CV; if you have been residing in Country in the last 3 years please provide the exact duration and motives of your stay and be prepared to provide the documentation proving it during the redress phase if required by the Project Manager). We strongly recommend you to use the Europass CV template.
  • Scanned copy of the certificate of the official academic qualification or proof of payment of the fees for the issuance of the certificate that allows the holder to access the doctoral studies. Students who hold Master degrees should present the scanned copies of their master's degrees. Students who are registered in an official university master's course that allows them to access the doctoral programme during the 2021/2022 academic year must present a scanned copy of their master's course registration form.
  • Scanned copy of academic transcript of the qualification equivalent to a bachelor's degree.
  • Scanned copy of academic transcript of the master's degree. Candidates who have not completed their Master's degrees must send their provisional academic transcript*.
  • Two signed and scanned reference letters. We will not contact the referees on your behalf.
  • A motivation letter, explaining his expertise and how the candidate is suited for the position she/he applies for.
  • Expressions of interest must be submitted to your account through https://bosomshield.eu/.
  • Researchers willing must apply to maximum two positions of the aforementioned 10 positions.
  • DCs will be pre-selected on the basis of internal evaluation.
  • Candidates will be informed of the results of the pre-selection two weeks after the deadline.
  • Interview between the highest ranked candidates of the pre-selection will be organed by the supervisors to select the final candidate.