Job Reference: 542_24_LS_LS_R2.
Closing Date: Monday, 30 September, 2024.
About BSC
The Barcelona Supercomputing Center - Centro Nacional de Supercomputación (BSC‑CNS) is the leading supercomputing center in Spain. It houses MareNostrum, one of the most powerful supercomputers in Europe, was a founding and hosting member of the former European HPC infrastructure PRACE (Partnership for Advanced Computing in Europe), and is now hosting entity for EuroHPC JU, the Joint Undertaking that leads large‑scale investments and HPC provision in Europe. The mission of BSC is to research, develop and manage information technologies in order to facilitate scientific progress. BSC combines HPC service provision and R&D into both computer and computational science (life, earth and engineering sciences) under one roof, and currently has over 1000 staff from 60 countries.
We promote Equity, Diversity and Inclusion, fostering an environment where each and every one of us is appreciated for who we are, regardless of our differences.
Context And Mission
The field of medical imaging is rapidly evolving, with several key trends emerging in 2024. Growth in Advanced Imaging Techniques, Rise of Hyperspectral and Molecular Imaging, Integration of AI and Machine Learning, Focus on Patient‑Centric Imaging and Emerging Technologies are just a few of the latest trends in Medical Imaging. New technologies are being developed to improve imaging quality and efficiency, including 3D imaging and other innovative modalities. Deep /Machine learning technology indicates a significant transformation in how medical imaging is conducted, with a strong emphasis on technology, patient care, and improved diagnostic capabilities. Deep learning is a cutting‑edge branch of artificial intelligence that empowers machines to learn from vast datasets and make intelligent decisions. By mimicking the structure and function of the human brain through artificial neural networks, deep learning algorithms excel at tasks such as image recognition, speech synthesis, and language translation. The Life Sciences department will incorporate a new research line to harness the potential of deep learning to drive innovation and solve complex problems across various domains using advanced Artificial Intelligence methods (Medical Imaging, Deep/Machine learning, Computer Vision, etc.). This new group is committed to boosting the power of advanced imaging technologies to improve healthcare outcomes. From X‑rays and MRI scans to CT scans and ultrasound, medical imaging plays a crucial role in diagnosis, treatment planning, and monitoring of various medical conditions. Through cutting‑edge research and innovation, we aim to push the boundaries of what is possible in medical imaging, developing new techniques and algorithms to enhance image quality, reduce radiation exposure, and increase diagnostic accuracy.
The funding for these actions/fellowships and contracts comes from the European Union Recovery and Resilience Facility - Next Generation, within the framework of the General Invitation by the public business entity Red.es to participate in the talent attraction and retention programs within Investment 4 of Component 19 of the Recovery, Transformation, and Resilience Plan.
Key Duties
- Participate actively in the research lines of the group.
- Contribute to writing research proposals.
- Publish research findings in top‑tier conferences and high‑impact journals.
- Supervise junior researchers and provide mentorship in their career path.
- Participate in technical meetings with internal and external collaborators.
- Promote scientific dissemination and scientific activities within a team.
Requirements
- PhD in artificial intelligence, machine learning, computer vision, computer science, computational biology, bioinformatics, physics, mathematics or related fields.
- Experience in image analysis, medical imaging and computer vision.
- Proven excellent scientific publication track record.
- Knowledge of UNIX/Linux environments.
- Proficiency in Python or equivalent programming languages.
- Deep knowledge in Deep learning frameworks (Pytorch, TensorFlow, Keras).
- Participation in National and European projects.
Additional Knowledge and Professional Experience
- Experience in Data science and Data‑centric methodologies (Uncertainty modeling, Noisy data, etc.).
La financiación de estas actuaciones/becas y contratos, procede del Mecanismo de Recuperación y Resiliencia de la Unión Europea-Next Generation, en el marco de la Invitación General de la entidad pública empresarial Red.es para participar en los programas de atracción y retención del talento dentro de la Inversión 4 del Componente 19 del Plan de Recuperación, Transformación y Resiliencia.
