We are looking for a content specialist who is eager to share his or her knowledge with the new generation. Would you like to join our team as a Computer Vision & Data Science Researcher?
As a passionate and experienced Computer Vision & Data Science expert, NHL Stenden offers you a unique opportunity: you can share your knowledge and expertise with committed and equally passionate students and work with them on practice-oriented research. With a treasure chest of facilities - from your own drones, supercomputer 'Deep Frisian' to one of the finest camera collections in the Netherlands - you help companies innovate with applicable academic knowledge. These facilities, combined with the knowledge in the field of Deep Learning, makes our lectorate powerful and the possibilities are endless.
Who are we?
Things happen by doing them. That is what we at NHL Stenden believe. We give our students the opportunity to develop their talents optimally. In a modern research environment, they themselves give direction to their studies and professional growth. We have strong ties with companies and institutions in the region, but also across the border. As an international multi-campus university of applied sciences, we encourage our students to look beyond their own field of study to develop new knowledge and participate in innovative projects. We create a meeting place where flows of knowledge and cultures come together and where new connections with the work field are created. In an ambitious way, NHL Stenden provides knowledge that works!
As a researcher, you will work at the Computer Vision & Data Science Knowledge Centre. The research group consists of 8 FTEs including 2 lecturers, Jaap van de Loosdrecht and Ioannis Katramados.
What does the position entail
As a Computer Vision & Data Science Researcher, you are an important link between our clients and our students. You make sure that students are prepared to strengthen the business world as innovative professionals. You act as a sounding board and you passionately involve the students with your knowledge and skills from practice. At the same time, you will work with the students on various real-life projects in the following areas: computer vision, data science, deep learning and hyperspectral imaging.
One of our successful projects was commissioned by an agency investigating innovations in healthcare: ‘Seam leakage’ after surgery is a worrisome problem. In the project, our lectorate looked for a measuring instrument that maps the quality of the tissue of the intestinal wall. Using the measuring instrument, the micro(blood) circulation of the tissue is made visible and this enables the operating surgeon to make a better decision with the ultimate goal of less 'seam leakage' after surgery. This means less intensive care and faster recovery for the patient.
Why will you be doing this
Because you're passionate about your field. You want to keep learning and researching and share that knowledge with our students, so that you can contribute to the quality of our education. We are working on the development of the HBO (higher vocational education) master Computer Vision & Data Science. You can contribute to this as well. This is because you are part of the development team, and in this role, you help develop solid teaching materials, among other things. This, in combination with coaching students and working on technological innovations in practice, makes this job so special and versatile. You become eager to see our wealth of industrial inspection cameras; from UV, VIS, NIR, SWIR and LWIR to hyperspectral. For the analysis of Big Data, we have our own supercomputer 'Deep Frisian' at our disposal, which provides more computing power than 100 common PCs!
What can you expect to do during a working day
It's Monday morning. You start the working week with your colleagues in a scrum meeting. You will discuss problems and challenges, but you will also reflect on the successes of last week. After the meeting, you have an appointment with a potential client. Afterwards, you start working on a quotation immediately. In the afternoon, you work from the mechanical recycling lab with three of your students and the Circular Plastics lectorate on the project for a local waste separation company. You are performing a plastic analysis with hyperspectral cameras. The goal? Even better recycling.
Yesterday, you read a scientific article about a method that might work well on this data, and you implement this method and test it together with your students that same afternoon. Over the course of this week, you will have a progress meeting with your client in which you include them in the developments realised. You regularly visit the client on location, but they also come to you regularly, like today. A wonderful opportunity to show what you have to offer. Your working day is almost over when you receive an e-mail with an agreement to your quotation. A new project can be set up. You will get started on this first thing tomorrow. You're looking forward to your next day at work.
These characteristics suit you:
Does a portion of the above characteristics apply to you? Then you are the Computer Vision & Data Science Researcher we need!
These are your employment conditions:
Just a few reasons to want to work with us
Do you recognise yourself in the profile? This is how you can apply for this position
NHL Stenden uses the services of Effectus-HR for the application procedure. Are you the ideal candidate who fits the above profile? Then hesitate no longer and apply immediately via de sollicitatieknop. A PAPI Personality Questionnaire will be used during the application procedure. For questions about the position and/or the procedure, please contact Marloes Peereboom (Effectus-HR recruiter) via phone number 06-47763816.
NHL Stenden and Effectus-HR are consciously and confidently working together to fill this vacancy. That is why Effectus-HR has been granted exclusivity for this vacancy. Given their completion rate of 93%, we are convinced that a more than suitable candidate will be found for this vacancy as well. Therefore, acquisition in response to this vacancy is neither necessary nor desirable.