OFFER DEADLINE :
30/09/2022 23:59:00 – Europe/Brussels
KTH Royal Institute of Technology
EU RESEARCH FRAMEWORK PROGRAMME:
HORIZON-MSCA-2021-DN-01-01 DEPARTMENT :
Department of Biomedical Engineering and Health Systems
Associate Prof. Rodrigo Moreno and Prof. Örjan Smedby, established at the at the Department of Biomedical Engineering and Health Systems at KTH Royal Institute of Technology (Stockholm, Sweden), are interested in receiving Expressions of Interest of potential candidates for the Marie Sklodowska – Curie Doctorate Network (MSCA-DN-2021) call.
The title of the proposed project: Machine learning and 3D mammography
Tomosynthesis is a promising 3D modality for diagnosing breast cancer. Deep learning is the most successful form of artificial intelligence (AI). The overarching goal of this project is to utilize a unique database of tomosynthesis and mammography images and new methods in deep learning to create novel diagnostic tools for breast cancer.
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 KTH core expertise.
KTH as Hosting Institution located at Scientific Campus of Flemingsberg (Stockholm, SE), has all the technical and scientific facilities for carry out this project, in close collaboration with Malmö University Hospital, located in Southern Sweden.
KTH Royal Institute of Technology in Stockholm has grown to become one of Europe’s leading technical and engineering universities, as well as a key centre of intellectual talent and innovation. We are Sweden’s largest technical research and learning institution and home to students, researchers and faculty from around the world. Our research and education covers a wide area including natural sciences and all branches of engineering, as well as architecture, industrial management, urban planning, history and philosophy.
The research group of Örjan Smedby and Rodrigo Moreno focuses on medical image processing, including analysis of neuroimaging, tumor imaging and imaging of the musculoskeletal system. Much of the research is based on modern techniques in machine learning, such as deep learning.
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.
During the selection process, candidates will be assessed upon their ability to:
- independently pursue his or her work,
- collaborate with others,
- have a professional approach and
- analyze and work with complex issues.
- 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:
HOW TO APPLY
- 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 the official KTH website at KTH. The announcement will appear on 8 Sept., with an application deadline of 29 Sept.
- Researchers willing must apply to maximum two positions of the aforementioned 10 positions.
- Doctoral candidates 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.