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anatomical models. These datasets will serve as the foundation for training robust 3D reconstruction networks, building on architectures such as Pix2Vox++, to infer the fetal aorta and ductus arteriosus from
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to the overall architecture of the project’s wireless neuromodulation system. About You You will have: A PhD (or equivalent) in Electrical Engineering, Electronics, Electromagnetics, Bioelectronics, or a related
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wearable sensors for resting breathing data collection. They will also ascertain whether the quality of home monitored data is suitable for SPAR analysis (in house software). Key responsibilities: Optimise
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. Ability to use computer algebra software (e.g. Mathematica or Maple) for symbolic computations 2. Good numerical skills 3. Experience in field-theoretical methods (e.g. supersymmetry) 4
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP
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. The project has a strong emphasis on software development; the candidate will develop and maintain workflows and datasets related to the project according to FAIR principles, supported by Dr Matta and KCL’s E
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integration and standards for bioimaging data Experience working in multidisciplinary teams and at the interface between biological data, biologists and data scientists/software engineers Strong communication
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validation/testing of novel mixed conducting materials. The project has a strong emphasis on software development; the candidate will develop and maintain workflows and datasets related to the project
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frameworks, or complex intervention development Experience or training in relevant software for qualitative research, such as NVivo Experience in the delivery and/or evaluation of clinical trials or complex
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, perinatal mental health, child health). High degree of competence in standard medical statistics and in using statistical software packages (e.g. R, Stata or Python). Experience working with large-scale