ORTEC
Job description
ORTEC leverages data and mathematics to create value for businesses and society at large. They develop a leading employee rostering solution for various industries. The optimization module creates schedules for employees such that hard constraints (e.g., labor rules) are not violated and soft constraints (e.g., preferences of employees and planners) are respected as much as possible.
The aim of this work is to evaluate the performance of the current optimizer and to look for possible improvements.
In a first step, the performance of our optimizer is compared to the state-of-the-art algorithms from literature using data sets from our clients. As a thesis student, you will study the most recent scientific literature on nurse scheduling algorithms. In most of the studies, benchmark instances are used. However, at ORTEC, we have found that our customers’ scheduling problems are a lot more complex than these benchmarks. For example, in healthcare, we must deal with many part-time employees and many scheduling preferences.
Afterwards, based on literature, your creativity and brainstorm sessions, you will design a new solution approach to the scheduling problem. You will implement this new approach in your preferred programming language (e.g. C# or Python) and this approach will be evaluated using our customer’s data.
Who you are
What we offer
The next steps:
Did we peak your interest? Then upload your CV, motivation letter and grade lists (BSc and MSc in one PDF if applicable). The recruitment process will consist of two online assessments: a personality and intelligence test, and an interview.
What to expect
We will help you to thrive in your field of expertise. We offer development programs, tailored to your individual needs and function requirements, including opportunities to attend courses and seminars. We offer challenging, practical hands-on experience with opportunities to work abroad. We operate in a flat organizational structure that keeps communication lines short. The atmosphere is open, informal, cooperative and positive.