Assistant Professor in Statistical Learning

16 May 2023
Job Information

Organisation/Company

Maastricht University (UM)

Research Field

Technology

Researcher Profile

Leading Researcher (R4)
Established Researcher (R3)

Country

Netherlands

Application Deadline

30 May 2023 - 21:59 (UTC)

Type of Contract

Temporary

Job Status

Not Applicable

Hours Per Week

38.0

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

The Department of Advanced Computing Sciences (DACS) is looking for an Assistant Professor in Statistical Learning. To strengthen our research initiatives on statistical learning, we are looking for a scientist with expertise in areas like: computational statistics, machine learning, data mining. Research on emerging statistical learning topics, for instance: foundation models, conformal prediction, causal discovery– is particularly welcome.

As our new colleague, you will contribute to DACS research. Our research activities span the entire spectrum from curiosity-driven research to responsible societal applications, often taking on an interdisciplinary character. Contributions to areas such as multi-agent systems, (medical) signal and image processing, FAIR principles, game theory, intelligent search techniques and affective computing are internationally recognized. What makes our research so interesting is that DACS maintains an industry network with over 80 private collaborators ranging from local SMEs to large multinationals. The department designs and develops data-driven solutions for a wide variety of business applications in sectors including transport and logistics, healthcare, and production and manufacturing. This why you can contribute to science and our society of tomorrow!

In addition to your research, you will contribute to our top-rated education. Our department offers one bachelor’s program and two master programs, all of which are nationally ranked among the top of their kind in the fields of AI and Data Science. In September 2023, we will also launch a new bachelor in Computer Science. You will strongly contribute to the focus and strengthening of our programs.

Requirements
Specific Requirements

Who are you?

We seek a colleague who is passionate about research and who enjoys teaching. You feel at home in a strongly international and diverse community like ours. Furthermore, we are looking to welcome someone who fosters collaboration at all levels.

Our ideal candidate has:

• A PhD degree in  Statistical Learning,  Computational Statistics, Statistics or a strongly related field;
• Preferably at least 2 years working experience in an academic environment post-PhD;
• A proven track record in research and teaching;
• Effective communication and organizational skills;
• Experience with funding acquisition at national and European level.

Additional Information
Benefits

What are we offering you?

We offer a position (1.0 FTE) as Assistant Professor for 18 months. Upon satisfactory performance, this position will become permanent.

We offer a salary as stipulated in the Collective Labour Agreement of the Dutch Universities (CAO-NU). Within this framework, we offer a competitive salary with a minimum of € 3.974 and a maximum of € 6.181 per month (depending on your experience) for a full-time position of 38 hours/week. On top of this, there is an annual holiday allowance (8% of annual income) and an annual end-of-year bonus (8.3% of annual income).

Applicants from outside The Netherlands may be eligible for the so-called 30% ruling, a tax cut for highly skilled migrants that applies for a maximum of five years. If you are moving to Maastricht from more than 40 kilometers away, you may qualify for a one-time reimbursement of your relocation costs

Besides that, the University offers excellent secondary work conditions. Notable terms include a pension scheme, an optional collective healthcare plan and partially paid parental leave. Furthermore, Maastricht University uses a selection model, which allows you to exchange employment conditions to adapt them to your preferences and circumstances. 

The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website www.maastrichtuniversity.nl  > About UM > Working at UM.

Selection process

Please send in the following documents:

• Research statement;
• Teaching statement;
• CV;
• List of publications;
• Contact information (names, e-mail addresses, and phone number) of two persons willing to provide references.

Send your application, stating the vacancy number AT2023.227, by email to:
[email protected]

Maastricht University is committed to promoting and nurturing a diverse and inclusive community. We believe that diversity in our staff and student population contributes to the quality of research and education at UM, and strive to enable this through inclusive policies and innovative projects led by teams of staff and students. We encourage you to apply for this position.

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Additional comments

If you have questions about this position, you can refer to:
Prof. dr. Mark Winands, Professor in Machine Reasoning
Chair of Department of Advanced Computing Sciences
E: [email protected]

If you are interested in the position of Assistant Professor in Statistical Learning, we welcome you to apply by pressing the 'apply now' button on this page to see the application procedure.

Please submit your application before May 31, 2023.

Website for additional job details

https://www.academictransfer.com/327777/

Work Location(s)

Number of offers available

1

Company/Institute

Maastricht University

Country

Netherlands

City

Maastricht

Postal Code

6229 EN

Street

Paul-Henri Spaaklaan 1

Where to apply

Website

https://www.academictransfer.com/327777/assistant-professor-in-statistical-lear…

Contact

City

Maastricht

Website

http://www.maastrichtuniversity.nl/

Street

Minderbroedersberg 4

Postal Code

6211 LK

STATUS: EXPIRED