The Institute for Neuroinformatics at ETH/UZH Zurich is collaborating with the Neurosurgery Department USZ to investigate neural networks in the field of machine learning and in patients with epilepsy. We are currently looking for a
PhD Student in Neural Networks
Deep learning has become a popular term in only three years. We will apply this and other methods of machine learning to develop a dedicated embedded electronic device that can quickly and reliably detect epileptogenic brain tissue from the intracranial EEG (iEEG) recordings of epilepsy patients. In particular, High-Frequency Oscillations (HFO) have been recently established as promising biomarkers to guide epilepsy surgery.
The candidate will be responsible for the computational and theoretical aspects of the project, which aims to find the optimal algorithms embodied in Spiking Neural Networks (SNN) for identifying HFO. The SNN have to be compatible with the mixed signal analog/digital neuromorphic computing devices that are available at our labs, and will have to provide specification for future generations of neuromorphic processors tailored to the detection of HFO in real-time, and using ultra-low power and compact CMOS chips.
The candidate will also participate in iEEG recordings. The candidate will spend time both at the Institute of Neuroinformatics and at the University Hospital Zurich.
INI offers advanced, interdisciplinary PhD training and participation in cutting-edge neuroscience and neuroinformatics research projects. The institute is home to a lively and interactive educational atmosphere and highly competitive salaries. Successful candidates will participate in the ZNZ Doctoral Program where they receive additional theoretical and practical training. Compensation/salary will be paid according to the guidelines of the Swiss National Science Foundation. Successful candidates will receive their PhD from the Faculty of Science at the University of Zurich.
You have a master degree in a Computer Science, Mathematics, Physics or related fields; solid programming skills; good written and spoken English; strong team-working abilities and excellent communication skills. Basic knowledge in experimental neuroscience is beneficial. Ideal candidates have a strong background in computational neuroscience models of cortical networks, and in recurrent/stochastic networks of spiking neurons for processing spatio-temporal patterns. Experience in reservoir computing, machine learning, deep learning, and probabilistic graphical models is useful. Fluent German would be a plus to speak with patients. Suitable candidates should have an intrinsic motivation to unravel neural algorithms of information processing and learning.
We look forward to receiving your online application including a letter of motivation, CV, diplomas and contact details of 2 referees. Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

For further information please visit our website www.ini.uzh.ch. Questions regarding the position should be directed to Prof. Giacomo Indiveri, giacomo@ini.uzh.ch or Prof. Johannes Sarnthein, johannes.sarnthein@usz.ch (no applications).