Full Professor of Theoretical Machine Learning and Neural Networks (0.8 - 1.0 FTE)
Full Professor of Theoretical Machine Learning and Neural Networks
Employment: 0.8 - 1.0 FTE
Gross monthly salary: € 5,843 - € 8,508
Faculty of Science
Required background: PhD
Application deadline: 15 November 2021
A world from which we demand more and more requires people who can make a contribution. Critical thinkers who will take a closer look at what is really important. As a Professor, you will perform leading research and teach students in the area of physics-based theoretical machine learning, to strengthen the role and visibility of the international Machine Learning landscape.
As successful candidate you will join the Department of Biophysics and perform internationally leading theoretical research in an area of physics-based theoretical machine learning. You are interested in the neuroscience research of the Donders Institute, and the DCN in particular, and will engage actively in interdisciplinary research collaborations with other research fields and/or internal or external partners. You will contribute to the teaching and the innovation of Radboud's popular theoretical machine learning courses, and possibly of other core undergraduate physics subjects that are taught at the Faculty of Science. You will supervise students' research projects at the Bachelor's, Master's and PhD levels. Finally, you will contribute to the effective administration of Radboud University and the acquisition of research funding, and will strengthen the role and visibility of Radboud University in the international Machine Learning landscape.
You hold a PhD degree in theoretical physics or applied mathematics.
You have a strong international research reputation in an area of physics-based theoretical machine learning and neural networks, as evidenced by a substantial publication track record.
You have a genuine affinity for academic teaching, and the ability to design undergraduate and postgraduate programmes as well as integrate research effectively into courses and projects.
You have at least five years of academic teaching experience following your PhD.
You have obtained a University Teaching Qualification or equivalent (or are committed to securing this qualification as soon as possible upon appointment).
You combine being a team player with strong leadership skills, specifically in terms of inspiring young scientists and in providing a research team with a clear sense of direction and purpose.
You have excellent communication skills, both verbally and in writing.
You have excellent administrative skills, and experience in the acquisition of research grants.
The Donders Institute for Brain, Cognition and Behaviour of Radboud University seeks to appoint a Professor of Theoretical Machine Learning and Neural Networks. The Donders Institute is a world-class research institute, housing more than 700 researchers devoted to understanding the mechanistic underpinnings of the human mind/brain. Research at the Donders Institute focuses on four themes:
Language and Communication
Action and Decision-making
Development and Lifelong Plasticity, and Natural Computation and Neurotechnology.
We have excellent and state-of-the-art research facilities available for a broad range of neuroscience research. The Donders Institute fosters a collaborative, multidisciplinary, supportive research environment with a diverse international staff. English is the lingua franca at the Institute.
You will join the academic staff of the Donders Center for Neuroscience (DCN) - one of the four Donders Centers at Radboud University's Faculty of Science. The Biophysics Department is part of the DCN. Neurophysicists at DCN mainly conduct experimental, theoretical and computational research into the principles of information processing by the brain, with particular focus on the mammalian auditory and visual systems. The Physics of Machine Learning and Complex Systems Group (https://acoolen24.wixsite.com/pmlcs) studies a broad range of theoretical topics, ranging from physics-based machine learning paradigms and quantum machine learning, via Bayesian inference and applications of statistical mechanics techniques in medical statistics, to network theory and the modelling of heterogeneous many-variable processes in physics and biology. The rationale behind this is that a deep theoretical understanding of machine learning and related topics may, in addition to its intrinsic merits, provide novel guiding principles with which to improve our understanding of computation in the brain, to make sense of the outstandingly complex datasets from neuroscience, and to aid the development of more effective inference and prediction algorithms for modern medicine. The group engages in multiple national and international research collaborations, and participates in several multidisciplinary initiatives that support machine learning research and teaching at Radboud University, such as Radboud-AI and the AI For Health ICAI Lab. Radboud University is also one of only three Dutch research units in the prestigious European ELLIS programme on learning and intelligent systems.
Radboud University actively supports equality, diversity and inclusion, and encourages applications from all sections of society. The university offers customised facilities to better align work and private life. Parents are entitled to partly paid parental leave and Radboud University employees enjoy flexibility in the way they structure their work. The university highly values the career development of its staff, which is facilitated by a variety of programmes. The Faculty of Science is an equal opportunity employer, committed to building a culturally diverse intellectual community, and as such encourages applications from women and minorities.
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!
Employment for 0.8 - 1.0 FTE.
An appoinment as an Associate Professor with the potential to further develop as a Full Professor is also possible. An Associate Professor will be employed as an Associate Professor level 2 (salary scale 13, maximum gross monthly salary of €6,421) or Associate Professor level 1 (salary scale 14, maximum gross monthly salary of €7,054), depending on your scientific track record and experience.
You will receive 8% holiday allowance and 8.3% end-of-year bonus.
It concerns a permanent employment.
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 29 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 Ton Coolen, Professor at +31 24 361 42 45 or email@example.com.
Practical information and applications
You can apply until 15 November 2021, exclusively using the button below. Kindly address your application to Ton Coolen. Please fill in the application form and attach the following documents:
Letter of motivation.
Publication list, with a motivated selection of your top five research papers.
Statement of current and future research plans.
Statement on teaching experience, including academic research supervision.
The first round of interviews will take place on 6 December. The second round will take place on 13 December. You would preferably begin employment on 2 May 2022.
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