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The Medical Image Inferencing and Distributed Diagnostics (MI2D2) research group in the Division of Biomedical Engineering (www.bme.uct.ac.za), University of Cape Town (UCT), South Africa and the LATIM (Medical Information Processing Laboratory), a joint research unit between University Hospital of Brest (CHRU), University of Brest (UBO), IMT Atlantique and INSERM in Brest, France, (http://latim.univ-brest.fr/) invite applications for a postdoctoral fellowship in machine learning/medical image processing. At UCT, South Africa, the position will be funded by the DST/NRF South African Research Chair in Biomedical Engineering & Innovation held by Prof. Tania Douglas for one year (2018 - 2019). The research will be supervised by Dr Tinashe Mutsvangwa and Prof. Douglas. In the LATIM, France, the fellowship will be supervised by Dr. Bhushan Borotikar, Prof. Valerie Burdin and Dr. Guillaume Dardenne and will be valid for 1.5 years (2018, 2019 – 2021). The position will be part of and funded by the FOLLOW-KNEE research project at Brest, France aimed at implementing an innovative solution for the treatment of osteoarthritis of the knee.
The objective of the position is to develop and make available to orthopaedic surgeons, a morphological and functional model of the knee. The purpose of this model is to predict, during the preoperative phase and for a given patient, the functional results of a surgical strategy for the placement of a total knee prosthesis. The modeling will be done from a heterogeneous database including MRI, CT, X-ray radiographs and kinematic data. The model will have to be deformed and adjusted according to specific data of the patient. The candidate is expected to run a research project autonomously; keenly follow new developments within the associated domain; and develop novel and innovative algorithms in medical image processing.
For more details and how to apply, please see the attachment.
The objective of the position is to develop and make available to orthopaedic surgeons, a morphological and functional model of the knee. The purpose of this model is to predict, during the preoperative phase and for a given patient, the functional results of a surgical strategy for the placement of a total knee prosthesis. The modeling will be done from a heterogeneous database including MRI, CT, X-ray radiographs and kinematic data. The model will have to be deformed and adjusted according to specific data of the patient. The candidate is expected to run a research project autonomously; keenly follow new developments within the associated domain; and develop novel and innovative algorithms in medical image processing.
For more details and how to apply, please see the attachment.