We live in a fast-changing world, where higher engineering education focusses on creating engineers that will deal with upcoming technological innovations. It is important to think ahead and educate engineers that could work on these problems and develop technological solutions for them, and are adaptable to deal with the changes in the world. This thesis focusses on how the master programme Applied Mathematics at the TU Delft could prepare their graduates for their professional career, by including adaptability in the curriculum. Adaptability is the ability to settle more easily in a new and unfamiliar environment, and to withstand changes in a changed environment or a new environment. Starting a new job after graduation is new, unfamiliar and unpredictable, so being adaptable could smoothen the transition from programme to labour market. The results of this thesis showed that two adaptive competencies, Dealing with Uncertain and Unpredictable Work situations, and Demonstrating Interpersonal Adaptability, were found to be most interested and relevant to include in the master programme. A tool was developed for the internship to make students more aware about these competencies, make them practice these competencies at their internship by developing personal learning goals and have them reflect on their experiences at the end. This tool could make the AM students more adaptive, what might prepare them for their professional career.

In this thesis, we consider levelling the number of required beds at the holding and recovery department. Due to the decreased number of available nurses, the workload for the nurses at hospitals has increased. For this reason, it is important to level the number of required beds at the holding and recovery department. By doing so, the workload can be reduced, beds will be available for emergency surgeries, less surgeries will be cancelled due to the lack of beds and less staff will be needed. The thesis starts with introducing an analytic calculation of the number of required beds at the holding and recovery department. These calculations consider a stochastic length of stay (LOS) distribution for each surgery type. Making use of the analytic calculation and the stochastic length of stay, several solution methods are developed. The first solution method includes a formulation of the problem as an Integer Linear Program (ILP). The exact calculation of the number of required beds is not linear, so the objective function is simplified. The ILP minimises the number of expected beds. The other solution methods uses the start and end times of each surgery. These start and end times are spread using two algorithms called Fixed Goal Values and Flexible Goal Values. Data from an Academic Medical Centre in the Netherlands is used to determine the LOS distributions and to find solutions for the ILP and the algorithms. This thesis shows that the number of required bed at the holding and recovery department can be reduced.