You cannot apply for this job anymore (deadline was 7 Nov 2021).
Browse the current job offers or choose an item in the top navigation above.
Do you want to contribute to innovative research for the field of neural data analysis? As a PhD candidate on machine learning algorithms, you will span the bridge between the fundamental research on machine learning and artificial intelligence, and applications. This will help us gain a better understanding into the mechanistic underpinnings of the human mind.
We invite applications for a PhD position on representation learning of electrophysiological brain data, supervised by Michael Tangermann. As a PhD candidate, you will be expected to contribute proactively to the Tangermann lab's research goals by developing advanced neural data processing algorithms in the context of closed-loop neurotechnological systems such as brain-computer interfaces.
On the algorithmic side, we will expect you to perform analyses on new or existing datasets, to investigate novel machine learning models and benchmark them against existing models, to evaluate hyper-parameters and architectures of models on a compute cluster, as well as visualise and present results.
On the application side, you will be expected to participate in the design of novel experimental protocols, to implement behavioural paradigms and experimental protocols in software, to program interfaces for real-time data access from hardware devices, to integrate software and hardware modules into closed-loop systems, to participate in recruiting healthy subjects for our studies, and to prepare and run experimental sessions with healthy subjects and patients.
Furthermore you will be expected to disseminate scientific results through high-impact papers in scientific journals, and by presenting your research at conferences and workshops. We also expect you to be committed to the values of open and reproducible science, including the publishing of well-documented code and datasets.
We offer you a full-time (100%) position for an overall duration of 4 years, subject to a favourable interim performance review. You will be employed at the Donders Institute for Brain, Cognition and Behaviour, where you will have the opportunity to collaborate and interact with renowned experts in the fields of artificial intelligence, psychology and cognitive neuroscience. You will also benefit from the extensive training programme offered by the Donders Graduate School. Additionally, you will have teaching duties and the opportunity to supervise MSc and BSc students during their thesis projects.
The following are essential requirements for this position:
Any of the following would be a plus:
Fixed-term contract: 4 years.
The Donders Institute for Brain, Cognition and Behaviour is a world-class interfaculty research centre that houses more than 700 researchers devoted to understanding the mechanistic underpinnings of the human mind. Research at the Donders Institute is focused around four themes: 1. Language and communication, 2. Perception, action and control, 3. Plasticity and memory, 4. Neural computation and neurotechnology. Excellent, state-of-the-art research facilities are available for the broad range of neuroscience research that is being conducted at the Donders Institute. The Donders Institute has been assessed by an international evaluation committee as 'excellent' and is recognised as a 'very stimulating environment for top researchers, as well as for young talent'. It fosters a collaborative, multidisciplinary, supportive research environment with a diverse international staff. English is the lingua franca at the Institute.
Donders' research groups are organised around PIs with a focused research topic. This PhD position is available within PI Michael Tangermann's group, which is investigating machine learning methods for the decoding of high-dimensional and noisy brain and behavioural signals and algorithms for closed-loop neurotechnological systems. Unsolved challenges in this respect are to compensate non-stationarity over time, to deal with small labelled training data sets and to transfer trained machine learning models between sessions, users and experimental protocols. Algorithm developments are regularly implemented and evaluated in closed-loop systems with health users and in clinical applications with patients. Examples are brain-computer interfaces for communication and control, human-robot interaction scenarios, systems supporting rehabilitation of stroke patients and adaptive deep brain stimulation systems. The research group emphasises mutual appreciation and collaboration, as the challenging topics under investigation require an interdisciplinary team effort.
You will be part of the Donders Graduate School for Cognitive Neuroscience.
Radboud University
We want to get the best out of science, others and ourselves. Why? Because this is what the world around us desperately needs. Leading research and education make an indispensable contribution to a healthy, free world with equal opportunities for all. This is what unites the more than 24,000 students and 5,600 employees at Radboud University. And this requires even more talent, collaboration and lifelong learning. You have a part to play!
We like to make it easy for you, sign in for these and other useful features: