PhD Candidate at the Donders Centre of Cognition: Closed-Loop Stimulus Optimisation: Combining Scene-Based Stimulation with Visual BCI

Employment

1.0 FTE

Gross monthly salary

€ 2,770 – € 3,539

Required background

Research University Degree

Organizational unit

Donders Centre for Cognitive Neuroimaging

Application deadline

03 March 2024

Apply now

Are you passionate about leveraging machine learning techniques to enhance neurotechnological systems such as brain-computer interfaces? Do you possess a solid foundation in mathematics and machine learning for scene analysis and for neural decoding? Are you comfortable with programming larger projects in the context of AI? If so, you are invited to become part of our European research consortium with esteemed partners from both academia and industry.
We are looking for a PhD candidate to set up and evaluate optimised brain-computer interface stimulus protocols with the human user in the loop. 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 in response to external stimuli. 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.
For multiple reasons, the individualisation of both stimulus characteristics and machine learning methods may be beneficial:
1) Individual users exhibit unique patterns of brain activity, necessitating the fine-tuning of experimental protocols to cater to each user’s specific needs. This adjustment is crucial for optimising the performance of BCIs.
2) As brain signals can change over time, the real-time adaptation of the individual stimulation parameters and decoding models may prevent a performance break-down.
3) Depending on the complexity of the scene that the user interacts with, different stimulation parameters and decoding approaches might be required.
Research on this individualisation is part of the goal to make BCI protocols more user-friendly, for example by using mostly imperceptible stimuli that integrate seamlessly into the scene. 
As a PhD candidate, you will be expected to integrate deep learning solutions for visual scene analysis and augmented reality into a larger BCI framework.  Additionally, you will investigate innovative experimental protocols and machine learning models and implement them in Python. To evaluate the new protocols and models, you will conduct non-invasive EEG studies with healthy participants. Furthermore, you will disseminate the 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 (100%) 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 your 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.

Profile

• You have obtained a Master’s degree in Artificial Intelligence, Computer Science, 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 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 deep learning.
• Ideally, you have already gained experience with C/C++/C# for interfacing with multimedia hardware.
• 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.

We are

The European Doctoral Network for Neural Prostheses and Brain Research (DONUT) is a 4-year EU-Horizon Europe Marie Sklodowska-Curie Doctoral Network project that is aimed to bring together leading experts from several European universities with the mission to provide a multidisciplinary and intersectoral Doctoral Network for talented young researchers (Doctoral Candidates). The network connects leading scientists and institutions with several industries over different research fields, providing opportunities for young researchers to gain experience in translational research in electroencephalography (EEG)-based measurements and Brain-Computer Interface (BCI) applications, healthcare, and industry. Its 10 doctoral candidates will address and solve deep problems in brain research, development of different BCI applications and systems with the latest technological advancements. 
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 recognised as a ‘very stimulating environment for top researchers, as well as for young talent’. The Donders Institute fosters a collaborative, multidisciplinary, supportive research environment with a diverse international staff. English is the lingua franca at the Institute.
The Data-Driven Neurotechnology lab is embedded in the Donders Institute for Brain, Cognition and Behaviour and in the department of Artificial Intelligence. Our research focuses on data-driven neurotechnology, i.e. domain-specific machine learning methods which allow to decode brain states in a single trial and methods which permit to modulate the ongoing brain state.

Radboud University
At Radboud University, we aim to make an impact through our work. We achieve this by conducting groundbreaking research, providing high-quality education, offering excellent support, and fostering collaborations within and outside the university. In doing so, we contribute indispensably to a healthy, free world with equal opportunities for all. To accomplish this, we need even more colleagues who, based on their expertise, are willing to search for answers. We advocate for an inclusive community and welcome employees with diverse backgrounds, cultures, and perspectives. Will you also contribute to making the world a little better? You have a part to play.
 
If you want to learn more about working at Radboud University, follow our Instagram account (link is external) and read stories from our colleagues.
We offer

• It concerns an employment for 1.0 FTE.
• The gross starting salary amounts to €2,541 per month based on a 38-hour working week, and will increase to €3,247 in the fourth year (salary scale P ).
• You will receive 8% holiday allowance and 8.3% end-of-year bonus.
• You will be employed for an initial period of 18 months, after which your performance will be evaluated. If the evaluation is positive, the contract will be extended by 2.5 years (4 year contract).
• You will be able to use our Dual Career and Family Care Services . Our Dual Career and Family Care Officer can assist you with family-related support, help your partner or spouse prepare for the local labour market, provide customized support in their search for employment and help your family settle in Nijmegen.
• Working for us means getting extra days off. In case of full-time employment, you can choose between 30 or 41 days of annual leave instead of the legally allotted 20.

Additional employment conditions
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.
Would you like more information?
For questions about the position, please contact Michael Tangermann, Associate Professor at [email protected] . Alternatively, you can contact Jordy Thielen, Assistant Professor at [email protected] .
Practical information and applying
You can apply until 3 March 2024, exclusively using the button below. Kindly address your application to Michael Tangermann. Please fill in the application form and attach the following documents:

• A motivation letter, including a short statement on whether you are applying for other DONUT positions as well, and whether your application might possibly be considered for other open DONUT PhD positions as well.
• Your CV, including a publication list, a list of own software repositories/projects, and the contact details of two references.
• A full transcript of grades, showing the courses, credits and grades of your BSc and MSc degrees (as well as an English translation). If you have not finished your degree yet, please provide a list that is as complete as possible.
• A two-page description of your MSc thesis or any other  scientific work you have completed, with a brief reasoning as to how it may connect to the topic of this PhD position.
• Proof of English proficiency (TOEFL, IELTS, CAE, TELC) if available.

The first round of interviews will take place on Friday 22 March. You would preferably begin employment as soon as possible.
We can imagine you’re curious about our application procedure . It offers a rough outline of what you can expect during the application process, how we handle your personal data and how we deal with internal and external candidates. If you wish to apply for a non-scientific position with a non-EU nationality, please take notice of the following information .
Apply now
Application deadline 03 March 2024

We would like to recruit our new colleague ourselves. Acquisition in response to this vacancy will not be appreciated.

Would you like more information?

Dr M.W. Tangermann (Michael)

Associate Professor

[email protected]

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You are an internal candidate if you:

• Work at Radboud University (i.e. have an employment contract with Radboud University).
• Are a former Radboud University employee receiving unemployment (WW/BWNU) benefits paid by Radboud University (which started less than two years ago or resulted from the discontinuation of your job/redundancy).
• Currently work as a student employee at Radboud University through the campus employment office.
• Work as a temporary employee at, or have been seconded to, Radboud University.

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Last modified:

20 February 2024

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