Are you an enthusiastic scientist and teacher with a broad knowledge of machine learning? Then you have a part to play as an Assistant Professor. Use your research to contribute to tackling real-life problems involving challenging learning tasks and/or data types and inspire the next generation of data scientists with your teaching. All while working in a friendly, dynamic work environment which offers ample room for both team science and individual initiative.

As an Assistant Professor of Machine Learning you will study, develop and apply machine learning techniques in order to tackle real-life problems involving challenging learning tasks and/or types of data. Examples of challenging tasks include the development of novel methods to infer causal relationships from observational data, or to predict the effect of medical interventions. You will have the opportunity to develop an independent line of research and to attract external research funding. 

You will be expected to supervise a number of PhD candidates, two of which will represent a start-up package provided by the university, and to teach courses in the Bachelor’s phase as well as courses related to your research expertise in the Data Science Master’s specialisation. You will also actively contribute to the supervision of Bachelor's and Master's projects and be involved in organisational tasks within the ELLIS unit.

• You are an enthusiastic scientist who holds a PhD and has a proven research record in machine learning, as evidenced by your publications. 
• You are a team player who enjoys collaborating with other scientists.
• You are keen to contribute to the application of your machine learning research in other domains.
• You have an engaging and open-minded attitude and are ready to contribute actively to a scientifically vibrant, productive, and interactive workplace, where people are respectful of each other and each other's ideas.
• You are able to set up your own research line and write successful grant applications.
• You are an enthusiastic teacher with excellent teaching skills, some teaching experience, and a willingness to teach software technology courses in the Bachelor’s phase as well as courses related to your research expertise in the Data Science Master’s specialisation. You enjoy interacting with students.
• You have a University Teaching Qualification (BKO, or equivalent qualification), or are willing to obtain one.
• You are able to help the section by contributing to organisational and management activities related to the research and education programme, and are willing to contribute to the management of the Radboud ELLIS unit.

Fixed-term contract: You will be appointed for an initial period of 18 months. Upon a positive performance evaluation at the end of this period, the contract may be converted into a permanent one.

• Employment for 0.8 - 1.0 FTE.
• The gross monthly salary amounts to a minimum of €4,629 and a maximum of €5,943 based on a 38-hour working week, depending on previous education and number of years of relevant work experience (salary scale 12). A preliminary scale may apply (salary scale 11).
• You will receive 8% holiday allowance and 8.3% end-of-year bonus.
• You will be appointed for an initial period of 18 months. Upon a positive performance evaluation at the end of this period, the contract may be converted into a permanent one.
• 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.

The position is available in the Data Science (DaS) group of the Institute for Computing and Information Sciences (iCIS) at Radboud University. The mission of the DaS group is to develop theories and methods for scalable machine learning and information retrieval to analyse big data and address challenging problems in science and society. 

We have expertise covering a broad range of topics concerning machine learning (causality, deep learning, Bayesian methods) and bridge the gap between theory and practice through collaboration with stakeholders from industry and other application domains. We put a special emphasis on responsible data science, focusing on innovations with a positive impact on society, and seeking to avoid harm.

The DaS group is part of the Radboud ELLIS unit, which brings together ongoing machine learning research at Radboud University and the Radboud university medical center and links this research to the international ELLIS ecosystem. The overarching theme of the Radboud ELLIS unit is 'AI for Life'.

Radboud University's Institute for Computing and Information Sciences is an internationally recognised institute, consistently ranked among the top Computer Science departments in the Netherlands. iCIS comprises an enthusiastic and devoted team of excellent academics that closely collaborate in a flat organisational structure. The institute focuses its research on three themes: data science, digital security, and software science, with the overall aim to contribute to both science and society. The themes span the full breadth from fundamental to application-oriented research. iCIS staff members are responsible for the Bachelor’s and Master’s programmes in computer science and information sciences, and contribute to the Bachelor’s and Master’s programmes in AI. The institute continuously strives to increase the diversity of its staff and has been particularly successful in attracting female staff. In 2017, iCIS received the Minerva award for gender and diversity from Informatics Europe. More than half of our scientific staff have an international background. 

Within the Radboud ELLIS unit, iCIS researchers closely collaborate with AI researchers from other faculties and the university hospital. The ELLIS unit organises regular events, encourages interactions among AI researchers, offers ELLIS fellowships to attract excellent Master’s students, and has links with local, national and international ecosystems.