Postdoctoral Research Fellow - Generative Video
Postdoctoral Research Fellow - Generative Video
EPFL - Swiss Federal Institute of Technology Lausanne
Geneva, Switzerland
Overview
We are seeking a post-doctoral researcher to work on a cutting-edge collaborative research project with a Swiss-US startup, Dandelion Science, and the Medical Image Processing Lab of the Ecole Polytechnique Fédérale de Lausanne (EPFL). The project will be headed by Prof. Dimitri Van De Ville and located at the Campus Biotech in Geneva, Switzerland.
The post-doctoral researcher will join a team of academic and industrial group members to work on developing new computational frameworks for generative AI and video analysis. This involves creating models to analyze and generate visual dynamics and link the visual dynamics to evoked neural dynamics. The role requires a mix of theoretical, algorithmic, and empirical work, collaborating closely with an industrial partner in the healthcare technology/AI field to bring the technology to market.
We are interested in maintaining the rich diversity in our work teams and encourage applications from all interested candidates. The salary range at EPFL is competitive and the quality of living in Switzerland is outstanding.
Qualifications
The ideal candidate will hold a Ph.D. in Computer Science, Electrical Engineering, or a related field, with a strong emphasis on generative image/video models, AI, and computer vision. They should have extensive experience in developing, implementing, training, and validating computational models and algorithms, particularly within the realms of generative video and machine learning. Proficiency in Python is essential, along with expertise in deep learning frameworks like PyTorch or TensorFlow. Familiarity with neuroimaging techniques and data analysis, particularly M/EEG, is a plus. The candidate should excel in problem-solving and possess the ability to work effectively within a multidisciplinary team. Strong English communication skills, both written and verbal, are crucial for articulating complex technical concepts and research findings.
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