PhD Position: Role of User Feedback and Introspection Mechanisms in the Context of Neurotechnological Systems

Are you passionate about leveraging machine learning techniques to enhance neurotechnological systems such as brain-computer interfaces? And are you interested in the psychology of learning and self-introspection? If so, join the European Doctoral Network for Neural Prostheses and Brain Research (DONUT) as PhD candidate!

We are looking for a PhD candidate to set up closed-loop brain-computer interface protocols and to evaluate brain signals and the task performance of users. This position needs to be filled as soon as possible.

Neurotechnological systems such as brain-computer interfaces (BCIs) allow to record and interpret the ongoing brain activity of healthy users or patients. This allows to design closed-loop applications for monitoring, for communication, for the control of devices or to support rehabilitation training. As brain signals are individual, noisy, and high-dimensional, machine learning methods play a crucial role in these systems.

Using a BCI system is not a natural skill. Thus not only the computer, but also the user undergoes a learning phase in order to produce more discriminative brain signals. In the case of BCI-supported rehabilitation training, this may comprise learning how to better use brain networks spared by a stroke, or how to generate specific brain responses that can be recognised by artificial intelligence methods. The PhD project investigates how healthy users and/or patients can be supported in the longitudinal learning of a BCI skill. The focus will be on how both experimental protocol design and machine learning methods can be optimised to provide enriched feedback in order to support the user’s self-introspection.

You will be expected to design and implement experimental protocols in Python to study the introspection ability of BCI users and the role of feedback. In our own labs or in clinics, you will conduct non-invasive EEG studies with healthy participants and patients, and cooperate with our clinical partners. Furthermore, you will train machine learning models to analyse the data and participate in the scientific dissemination of results in high-impact scientific journals, conferences and workshops. In addition we expect an attitude towards open and reproducible science, which includes the publishing of well-documented code and FAIR datasets. An excellent command of English is required, as this is the working language in our international lab.

We offer a full time position for an overall duration of four years. Throughout the project, you will receive guidance from Dr Michael Tangermann and Dr Jordy Thielen and be an integral part of the Data-Driven Neurotechnology Lab. The lab is situated within the AI department of the Donders Institute, offering additional opportunities for collaboration with experts in artificial intelligence, cognitive neuroscience, visual perception, and other relevant fields. You will also benefit from the extensive training programmes offered by the Donders Graduate School and the European doctoral training network DONUT (https://donut-project.eu/). In addition, you will benefit from multi-month research stays at DONUT’s academic and industrial partners' labs, which require mobility.

You must comply with the following mobility rule: you must not have resided or carried out their main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 36 months immediately before the recruitment date. You will be part of the Donders Graduate School for Cognitive Neuroscience and the European Doctoral Network for Neural Prostheses and Brain Research.

Your teaching load may be up to 10% of your working time.

Requirements:

• You have obtained a Master's degree in Artificial Intelligence, Computer Science, Cognitive Neuroscience or a related discipline.
• You fulfil the mobility rule for European doctoral networks: You have not resided or carried out your main activity (work, studies, etc.) in the Netherlands for more than 12 months in the 36 months immediately before the application deadline.
• You have a strong interest in neurotechnological systems such as brain-computer interfaces.
• You have a strong interest in neuroscience and self-introspection.
• You have a passion for research.
• You have enthusiasm and the ability to work in an international team.
• You have an excellent background in mathematics and machine learning.
• You have strong Python programming skills, and you are familiar with libraries for neuroimaging data as well as for machine learning.
• You know how to collaborate on larger software projects and are familiar with tools and infrastructure such as compute clusters, version control, etc.
• You have experience with dealing with neuroscientific data (e.g. from EEGs).
• You possess excellent written and spoken English language skills.

Salary Benefits:

• We will give you a temporary employment contract (1.0 FTE) of 1,5 years, after which your performance will be evaluated. If the evaluation is positive, your contract will be extended by 2.5 years (4-year contract).
• You will receive a starting salary of €2,770 gross per month based on a 38-hour working week, which will increase to €3,539 in the fourth year (salary scale P).
• You will receive an 8% holiday allowance and an 8,3% end-of-year bonus.
• You will be able to use our Dual Career and Family Support Service. The Dual Career Programme assists your partner via support, tools, and resources to improve their chances of independently finding employment in the Netherlands. Our Family Support Service helps you and your partner feel welcome and at home by providing customised assistance in navigating local facilities, schools, and amenities. Also take a look at our support for international staff page to discover all our services for international employees.
• You will receive extra days off. With full-time employment, you can choose between 30 or 41 days of annual leave instead of the statutory 20.

Work and science require good employment practices. This is reflected in Radboud University's primary and secondary employment conditions. You can make arrangements for the best possible work-life balance with flexible working hours, various leave arrangements and working from home. You are also able to compose part of your employment conditions yourself, for example, exchange income for extra leave days and receive a reimbursement for your sports subscription. And of course, we offer a good pension plan. You are given plenty of room and responsibility to develop your talents and realise your ambitions. Therefore, we provide various training and development schemes.

38 hours per week

Houtlaan 4