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… 73 / 32,89 fte Total staff excl. academic hospital 73 / 32,89 fte SHE Collaborates 9 / 6,85 fte SHE Educates 64 /4,03 fte Total FTE excl support Research, Collaborates 37,43 fte and Educates staff External PhD students 106 Honorary professor 7 Visiting fellows/professors nb FUNDING Funding 2023 Fte % (1) Direct funding 15,15 40,48% (2) Research grants 8,60 22,98% (3) Contract research 2,00 5,34% (4) Other 11,68 31,20% Total 37,43 100,0% TURNOVER Turnover 2023 (x1000) € % Government funding … in Qualitative Research (November 2023) JMHPE - Joint online HPE programme with Suez Canal University Egypt Certificate Course Organization & Leadership (2023) Germany 1 Canada 1 USA 1 Chile 1 Nederland 1 Total number of participants 5 4C/ID Workshop June (November cancelled) 2023 Canada 1 Netherlands 10 Total number of participants 11 Certificate Course Curriculum & Instruction (2023) Slovakia 1 Switserland 3 Rwanda 1 USA 1 The Netherlands 3 Republic of Moldova 1 Australia 1 Ireland 1 Total … (WITS), South Africa • University of Namibia (UNAM), Namibia • Welwitchia Health Training Centre, Namibia • Maastricht University (UM), the Netherlands • University of Turku, Finland In March 2023, SHE’s Prof. Jascha de Nooijer and Rikus Nieuwenhuis visited the partners to discuss, view and explore opportunities in Interprofessional Education and Collaborative Practice (IPECP). Please watch for an impression. In July 2023, Abigail Dreyer (WITS) attended the Summercourse at SHE. She was accompanied …

… MUMC+ Ophthalmologist H.J.M. Beckers FHML: Faculty of Health, Medicine and Life Sciences Oprichting PEYEONEER Medtech B.V. Chief Medical Officer (CMO) PEYONEER Medtech B.V. H.J.M. Beckers FHML: Faculty of Health, Medicine and Life Sciences Stichting Visitatie NOG Chair H.J.M. Beckers FHML: Faculty of Health, Medicine and Life Sciences Concilium Ophthalmologicum Neerlandicum Chair A. Beckers FDR: Faculteit der Rechtsgeleerdheid Hart Publishing Oxford Editor of a newly established book series The … IMFO Docent A.H.H. Bollen FDR: Faculteit der Rechtsgeleerdheid Tuchtcollege NOAB Lid Tuchtcollege A.H.H. Bollen FDR: Faculteit der Rechtsgeleerdheid Kluwer auteur A.H.H. Bollen FDR: Faculteit der Rechtsgeleerdheid Universiteit van Aruba Visiting professor A.H.H. Bollen FDR: Faculteit der Rechtsgeleerdheid Hogeschool Fontys - Venlo Member of Expert team of Lectoraat Cross-Border Business Developlment M.L. Bonte FPN: Faculty of Psychology and Neuroscience Nederlands Kwaliteitsinstituut … and Economics Tilburg University Gak institute: Professor Pension communication and Choice Guidance E.C. Brüggen School of Business and Economics Nibud Member of the supervisory board E.C. Brüggen School of Business and Economics Erasmus Universiteit Visiting lecturer, Certified Pensioenexecutive Program E.C. Brüggen School of Business and Economics Stichting Pensioenfonds Medisch Specialisten Member of the policy advisory committee on pensions J.S. Burgers FHML: Faculty of Health, Medicine and …

… techniques and will require them to read and understand published scientific papers from recent Machine Learning conferences. Prerequisites Desired Prior Knowledge: Machine Learning Recommended reading Pattern Recognition and Machine Learning - C.M. Bishop; Bayesian Reasoning and Machine Learning - D. Barber; Gaussian Processes for Machine Learning - C.E. Rasmussen & C. Williams; The Elements of Statistical Learning - T. Hastie et al. KEN4154 Period 2 28 Oct 2024 13 Dec 2024 Print course description … There are often constraints on the order in which tasks, or ‘jobs’ can be performed, and there are usually capacity constraints of the machines. This leads to natural, industrially critical optimization problems. For example, a company might choose to buy many machines to process jobs, but then there is a risk that the machines will be underused, which is economically inefficient. On the other hand, too few machines, or an inappropriate ordering of tasks, may lead to machines spending a significant … tasks. In this course, we look at various mathematical models and techniques for optimizing planning and scheduling problems, subject to different optimality criteria. We will discuss, among others, single-machine models, parallel-machine models, job-shop models, and algorithms for planning and scheduling (exact, approximate, heuristic) and we also touch upon the computational complexity (distinguishing between ‘easy’ and ‘difficult’ problems) of the underlying problems. Last but not least, we will …