Machine Learning Engineer

We are looking for a Machine Learning Engineer who will help us expand the intelligence behind CTcue!

About CTcue

We live in a world where most information is readily available at our fingertips. You might be surprised to learn that the situation in hospitals is rather different. Initially we started CTcue, because we wanted to help doctors identify patients for clinical trials in an automated manner. However, along the way of actualizing this, we gradually started to realize that our job is far more fundamental than that.

Due to the complexity of EHR data, it doesn’t lend itself well for automated analysis. A key factor in this complexity is that a large part of the valuable information is recorded as text (notes, referral letters, questionnaires). We’re now building a data platform where, using the latest machine learning technologies, this unstructured data is organized and combined with the structured data sources of the EHRs. Furthermore, our platform includes two state-of-the-art applications for identifying patient cohorts based on certain criteria and for collecting clinical data.

In all that we do, we have the doctors and patients at the fore of our mind, and we also make sure to strictly adhere to privacy regulations. CTcue is currently used on a daily basis by 20+ hospitals in The Netherlands and in Belgium.

What are you going to do?

As an AI engineer you will apply machine learning algorithms to the unstructured data of EHRs. You make use of the latest research to create machine learning tools that will enhance the experience of our users. What you do has a strong impact on the success of our product.

Together with Lydia and Reinier you will form a small and self-organising team. The three of you are responsible for building the infrastructure, implementing the algorithms and converting them to production ready models. EHR data is highly messy, so you must be prepared to getting your hands dirty on this. You will process and cleanse the data from a wide variety of sources and you will then transform and convert the unstructured data set into structured data for our products.

Here are some example projects that our AI team is working on right now:

Finally, you will be part of a larger cross-functional dynamic team consisting of developers, designers, product owners and data engineers. We are user (i.e. doctor) focused, have an experimental mindset and we iterate quickly.

What does a typical AI workday at CTcue look like?

In the morning you have a brainstorm with the developers, data engineers and the product owners about how to improve features. You’ll then work individually on one of our big projects such as normalization of medical concepts or bulk validation. You’ll discuss with Reinier and Lydia how to gather the data you need in an efficient way and you conclude the day by reading research papers in order to find a solution for a complex problem that was bugging you last week.

Your profile

If you feel you are up for this challenge, contact us to get a coffee sometime soon. We look forward to meeting you!

To apply for this Machine learning engineer position or if you want to find out more first please contact Lydia Mennes for a chat on 085 600 1037 or send an e-mail to lydia@ctcue.com

CTcue is not able to make any Visa/Working permit arrangements.