Associate / Assistant Professor of Machine Learning for Data Science

Radboud University

Netherlands

Associate and Assistant Professor (Tenure Track) Positions in Machine Learning for Data Science

  • 32 - 40 hours per week
  • Faculty of Science
  • Job level: PhD
  • Duration of the contract: according to position
  • Application deadline: 31 March 2020

We are looking for

To strengthen and expand the Data Science section's research, we seek to appoint an Assistant Professor and an Associate Professor in Machine Learning for Data Science. Also, these positions will be pivotal for supporting our Bachelor's programme and our Data Science Master's specialisations, in particular for Master's courses that attract many students. The main goal of Machine Learning for Data Science is to develop machine learning approaches and techniques of broader applicability outside a specific application domain. Machine Learning for Data Science involves the study, development and application of machine learning techniques in order to tackle real-life problems involving challenging learning tasks and/or type of data.

Applicants for these positions are expected to have an active research programme and a commitment to teaching excellence. You should be a enthusiastic scientist with a background in machine learning for data science. You should be able to link your expertise with the current expertise of the Data Science section.

We ask

Profile for Associate Professor

  • Research: You are an enthusiastic scientist (PhD) with a broad knowledge of computer science and an established track record in research in machine learning for data science, as evidenced by your publications, invitations to scientific conferences and events, program committee memberships and research grant applications. You pursue an independent line of research, and have successfully applied for external funding. You are a team player who enjoys working with other scientists, and are able to build bridges between different disciplines. You are open to contributing to the application of your research in machine learning for data science in industry and society. You have an engaging and open-minded attitude and are willing to contribute actively to a scientifically vibrant, productive and interactive workplace where people are respectful of each other and each other's ideas.
  • Teaching: You are an enthusiastic teacher with established teaching skills and broad teaching experience, a clear vision on teaching, and a willingness 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 enjoy interacting with students.
  • Management: You have some experience in contributing to the management of research groups, including a proven record in successfully supervising PhD students.


Profile for Assistant Professor

  • Research: You are an enthusiastic scientist (PhD) with a proven research record in machine learning for data science, as evidenced, for instance, by your publications. You have the ability to develop an independent line of research, and to attract external research funding. You are a team player who enjoys collaborating with other scientists. You are open to contributing to the application of your research in machine learning for data science in industry and society. You have an engaging and open-minded attitude and are willing to contribute actively to a scientifically vibrant, productive and interactive workplace where people are respectful of each other and each other's ideas.
  • Teaching: You are an enthusiastic teacher with good teaching skills, some teaching experience, and a willingness 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 enjoy interacting with students.
  • Management: You are able to help the section by contributing to organisation and management activities related to our research and education programme.

We are

You will be appointed at the Data Science section of the Institute for Computing and Information Sciences (iCIS). Radboud University's iCIS is an internationally recognised institute, consistently ranked among the top Computer Science departments in the Netherlands. The institute focuses its research on three themes: Data Science, Digital Security and Software Science. In recent evaluations, iCIS has been consistently ranked as the No. 1 Computing Science department in the Netherlands. Evaluation committees praised our flat and open organisational structure, our ability to attract external funding, our strong ties to other disciplines, and our solid contacts with government and industrial partners. iCIS research in Data Science involves artificial intelligence and information retrieval: the use of machine learning and search technologies to understand and design intelligent systems that can learn from data and to improve access to, and representation of, information. Our group has expertise covering a broad range of topics concerning machine learning (causality, deep learning, Bayesian methods, Gaussian processes) and information retrieval (recommender systems, big data, web search engines, federated search, multimedia data analysis). We 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 Faculty of Science is a complete science faculty where research and education are closely related. The faculty aims to be an academic community with an international character, where staff members from different backgrounds combine their talents with the common goal of being a leading faculty of science in Europe.

Radboud University is an equal opportunity employer, committed to building a culturally diverse intellectual community, and as such encourages applications from women and minorities. The university offers customised facilities to better align work and private life. Parents are entitled to partly paid parental leave and RU 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.


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 22,000 students and 5,000 employees at Radboud University. And this requires even more talent and collaboration. You have a part to play!

We offer

  • Employment: 32 - 40 hours per week.
  • Associate Professor: you will be employed as an Associate Professor level 2 (salary scale 13, maximum gross monthly salary of €6,133) or Associate Professor level 1 (salary scale 14, maximum gross monthly salary of €6,738), depending on your scientific track record and experience. Duration of the contract: to be determined by mutual agreement.
  • Assistant Professor: at the start of your tenure track you will be employed as an Assistant Professor level 2 (salary scale 11, maximum gross monthly salary of €4,978) for a six-year period. If evaluated positively, you will be appointed as an Assistant Professor level 1 (salary scale 12, maximum gross monthly salary of €5,656) on the basis of a permanent contract. Further information on a tenure track at the Faculty of Science can be found here.
  • In addition to the salary: an 8% holiday allowance and an 8.3% end-of-year bonus.
  • You will be able to make use of our Dual Career Service: our Dual Career Officer will assist with family-related support, such as child care, and help your partner prepare for the local labour market and with finding an occupation.
  • Are you interested in our excellent employment conditions?

Would you like more information?

For more information about this vacancy, please contact:
Djoerd Hiemstra, Full Professor
Tel.: +31 24 3652719
Email: djoerd.hiemstra@ru.nl

Elena Marchiori, Full Professor
Tel.: +31 24 3652647
Email: elena.marchiori@ru.nl

Apply directly

Please address your application to Djoerd Hiemstra and submit it, using the application button, no later than 31 March 2020, 23:59 Amsterdam Time Zone.   

Your application should include the following attachments:

  • Letter of motivation. Please state the position you apply for at the beginning.
  • CV with the names of three referees, including at least one referee for teaching qualifications.
  • A teaching statement.
  • A research statement including a list of publications.

We drafted this vacancy to find and hire our new colleague ourselves. Recruitment agencies are kindly requested to refrain from responding.


In your application, please refer to Polytechnicpositions.com

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