ORTEC
Job description
ORTEC leverage data et mathematics to create value for businesses and society at large. They have a leading employee rostering solution for various industries. One of the possible rostering methods is self-rostering, where the employees express their preferences, compare them to the duty capacities and interchange shifts to define an initial roster. As the collaboration of the employees is not negligible, ORTEC would like to invest if we can use AI to make the process less time-consuming for the employees.
The aim of this work is to invest if we can use AI to make the process less time-consuming for the employees. In a very first step we would like to develop a machine learning model that proposes preferences for the nurses. The employees can make changes manually and the model can learn from that feedback. In a second step, we would like to propose changes to the nurses to satisfy the duty capacities. The acceptance or decline of the employees gives feedback about the propositions of the model.
As a thesis student, you will study the scientific literature related to self-rostering and machine learning. You will use SQL and Python to investigate actual company data. You will develop and fit machine learning models for the two steps mentioned above.
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.