Recrutement : Post Doctoral Researcher – Signal processing

Subject : Post-doctoral fellow (M/F) signal processing, AI and software for a closed-loop epilepsy treatment application using focal cooling, seizure prediction and detection.Level : Post-doc Contract length : 24 months renewable Place : Clinatec – bat 43 – 17 avenue des Martyrs – 38054 Grenoble Cedex Host-organization : Fonds de dotation Clinatec – https://www.clinatec.fr Contact : Malvina Billères – malvina.billeres@cea.fr
Context : Epilepsy remains one of the most common neurological disease. This pathology has an incidence of 50 to 100 000 new cases per year and affects around 50 million people worldwide.Antiepileptics drugs are currently the gold treatment but they are effective only in 60-70% of patients. For several years, nonpharmacological potential new treatments have been investigated including an interesting new approach using focal cooling. In the literature, some results in preclinical models have shown that a cooling at 21°C can reduce the frequency of epileptic seizures. The postdoctoral fellowship will be carried out at Clinatec, in Grenoble, France. We have started a programme focused on focal cooling treatment. Our aim is to develop a medical device delivering a focal cooling to deep brain regions such as the hippocampus to treat epilepsy. We have therefore developed a preclinical implantable device to deliver this cooling in order to obtain information concerning the parameters needed to reduce seizures (target temperature, duration…). The fellowship will investigate algorithmic approaches to detecting pre-ictal phenomena (interictal spikes) associated with the occurrence of seizures, using the PNH-penicillin model or other acute models. Seizure prediction is an essential part of the cooling approach-maximizing efficacy while reducing technical constraints. The candidate will work closely with a neurosurgeon, who will provide neuroscientigic expertise, as well as a PhD student (biology). The laboratory also includes engineers, clinicians and a signal processing team. Missions will include :
  • Labelling of the different brain signals occurring in epilepsy (seizure, pre-ictal, interictal, post-ictal…).
  • Statistical analysis and hypothesis testing of the data.
  • Online closed loop optimization of seizure prediction/forecasting algorithms.
  • Detection of anomalies (HFO, fast ripples, phase coupling) for prediction and forecasting.
  • Testing of adaptive algorithms for prediction and forecasting (preclinical/clinical database): effects of cooling on algorithm performance.
  • Integration of other measurements (temperature…) in algorithm prediction.
  • Maintenance and improvement of experiment software
Profil of candidate :  PhD or equivalent with strong knowledge in time-series, machine learning, signal processing, with strong skills in Python. Some experience in manipulating large data and working on clusters (slurm) is an advantage. Otherwise, a basic knowledge of the Unix command line basics is required. Ability to work autonomously. Location : The position is to be filled on the site of Clinatec, research center Ed. J. Safra, Grenoble. Clinatec is a biomedical research centre bringing together doctors, biologists and specialists in micro and nanotechnology. With nearly eighty researchers and employees, it is presented at its opening at the end of 2011 as the first centre of its kind in the world. With six hospital rooms and state-of-the-art medical imaging equipment as well as a state-of-the-art operating room, Clinatec has been developed by the Technological Research Directorate of the Commissariat à l’énergie atomique et aux énergies alternatives, CHU Grenoble Alpes, Fonds de dotation Clinatec and the University of Grenoble Alpes and works primarily on cancer, neurodegenerative diseases and disabilities. The main purpose of the Clinatec Endowment Fund is the implementation of any non-profit general interest action contributing to the promotion of Clinatec’s activities, in particular those relating to the advancement of research and the development of technological innovations for health.

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