Researcher Machine Learning and Optimization - Sustainable Buildings
Your research skills will help us to create a sustainable society!
Do you like data and are you a driven researcher who wants to contribute to making the Netherlands more sustainable in a practical way? Then we would like to welcome you to our team, where the use of data is the key to sustainable solutions for the energy transition! As Researcher Machine Learning and Optimization, you will have the opportunity to combine your passion for data, machine learning and sustainability.
This is you
As a researcher, you have broad interests, are tenacious and flexible and you take initiative. You do not only have a keen eye for the latest developments in machine learning and optimization, but also for its practical application. With a background in data science (Master or PhD) or an engineering degree (Master or PHD in Applied Physics, Mechanical Engineering, Electrical Engineering) with experience in the area of systems and control, you are ready to apply your research domain to concrete challenges for the design and operation of sustainable buildings.
Working with various teams within our company, you will initiate new solutions and concepts. You listen to colleagues and clients, moving with changing market demands while keeping an eye on long-term opportunities
How does your workweek look like?
- Developing algorithms to predict maintenance of building installations or monitor energy performance.
- Or that new customer demand that we don't know yet either.
- We always have students around that definitely appreciate good supervision.
- You go along to a meeting with a client where you demonstrate your solution with verve.
Your team
You work alternately with colleagues from our team who work on solutions for parametric design and with colleagues working on the development of our monitoring platform 'Bright Building'. We do not have a separate research department, but we work with 'embedded' research. Together with a senior researcher, you will bring this field into fruition.
And this is us
We are DWA. Designers of the world of tomorrow. Forerunners in making buildings, neighborhoods and areas natural gas-free. Pioneers in applying machine learning and digital twins, which we use to predict and optimize building performance. Our advice and designs answer important questions, with workable solutions. We dig deep to discover expectations and stay involved until we deliver.
Making sustainability work, that is our motto. We put this into practice every day with 150 enthusiastic, talented and driven employees. From a shared passion for sustainability and a great sense of responsibility. Together, we build a world that remains safe, healthy and livable, also for future generations. Everything we do is aimed at continuity. Continuity of our living environment, of performance and of relationships.
Above all, we leave our colleagues free to do what they are good at. With a score of no less than 89%, we can proudly call ourselves a 'certified Great Place To Work'. Our colleagues particularly appreciate the healthy work-life balance, the trust and freedom they are given in their work and the genuine passion for sustainability within the organization.
Interested in this vacancy?
Perhaps you still have questions, would first like to have an exploratory talk or a taster day. If so, then please contact at or at . Of course, you can also apply directly via or the application button
Our introduction program has been carefully put together; we will gladly show you the way and guide you in projects and your development. You will be assigned a buddy and mentor at DWA and you will be able to follow training in our own DWA Academy.
Functie: | researcher machine learning optimization |
Startdatum: | 21-12-2023 |
Ervaring: | Ervaren |
Educatielevel: | HBO |
Contracttype: | Vast |
Salaris: | onbekend – onbekend |
Uren per week: | 1 – 40 |
Heb je interesse in deze vacature en wil je graag op deze functie solliciteren? Neem dan contact op met DWA via onbekend of onbekend. Of bezoek hun website onbekend.
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