Job

Internship | Effective Explainable Artificial Intelligence for Machine Learning

Location

Soesterberg

Education type

university (wo)

Type

Internship and graduation project

Hours a week

Fulltime – 40

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What will you be doing?

In this internship you get the opportunity to develop state of the art methods to generate explanations about Machine Learning (ML) models for end-users. You do this in a small team of experts on Explainable AI (XAI) and Machine Learning, both within and outside TNO. By discussing explanation methods with potential end-users you obtain firsthand experience of what it means to use a ML system that is highly accurate, but also complex and opaque. As such you get the opportunity to build a new method, or extend existing ones, to obtain an impressive, information rich and helpful explanation about outputs from a ML system.

You get the chance to implement, train and validate a ML system on real-world data for TNO’s partner in this research; ABN Amro. ABN Amro will provide the use case and the data, but also researchers to help you build and deploy a ML system. As such you will have regular contact with them, to make sure you have everything you need for your research but also to get input what kind of explanations are valued.

You will implement your explanation method in TNO’s toolbox for XAI, to guarantee that your method will be used by other researches and TNO partners across industries. In addition we will support and motivate you to write a research paper out of this work, and might attend an international conference on ML to present your work.

What do we require of you?

You are a student in the final stages of your master in Artificial Intelligence, Computer Science, Datascience, or a similar study. With a record in Machine Learning (ML) and an affinity to make ML models usable for users that are experts in their domain, but not necessarily in ML. You have both a practical and theoretical knowledge of ML, experience with Python and common ML tools herein, and a pragmatic can-do mentality. In addition we value a research driven approach, good communication skills and the confidence to work closely with a TNO research partner.

What can you expect of your work situation?

Your internship will take place within the Perceptual & Cognitive Systems department of TNO, within the Human-Agent/Robot Teaming (HART) group. Our group exists out of 15 enthusiastic researchers that focus on connecting humans with AI, whether physical (e.g., robots or teleoperation) or virtual (decision support systems or e-partners). Specifically within the field of Explainable AI we not only develop state of the art methods, but also validate them with actual end-users.

Our department is located at TNO Soesterberg, which often organizes activities such as drinks, laser-gaming, boardgame nights, and more. In addition, you will have the opportunity to informally meet and work with TNO researchers but also other interns which may work on completely other research projects than you.

What can TNO offer you?

You want to work on the precursor of your career, an internship provides you with the opportunity to take a good look at your prospective future employer. TNO also goes a step further. It’s not just looking that interests us, you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your internship, and be given the scope for you to exceed yourself and your expectations. We also provide suitable compensation for internships. Click here to find more info about internships at TNO.

Application process

For this vacancy it is required that the AIVD issues a security clearance after conducting a security screening. Please visit for more information the AIVD website

Has this vacancy sparked your interest?

Then please feel free to apply on this vacancy! For further questions don’t hesitate to contact us.


Contact: Jasper Waa, van der
Phone number: +31 (0)6-115 39895



Note that applications via email and third party applications are not taken into consideration.

Interested?

Apply now

Apply

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