Are you an interested in data-driven optimization, and intelligent decision support through methods of Artificial Intelligence? Do you like the idea of working with techniques like Neural Networks, Evolutionary Computation, Swarm Intelligence, and fuzzy reasoning? Are you interested in applying your research in biomedical fields? We are looking for a PhD student in Information Systems/Business Intelligence with a focus on those topics.
Modern laboratory experiments in bio-medical disciplines generate large amounts of structured heterogeneous data. This data can be used to create models able to assist critical decisions in clinical environments. However, in order to be adopted in real-world scenarios, such models must be explainable, i.e., domain experts must be able to inspect and understand the rationale underlying decisions.
The PhD project will focus on the development of methodologies for the data-driven inference of decision support systems that can be inspected, trusted and even extended by domain experts. Such models must be explainable in nature and still provide a good fitting with respect to data. Moreover, although a model can be built out of data, an excessive complexity of the system can hamper its interpretability and, in turn, prevent any comprehension of the rationale of decisions. Thus, complexity reduction, feature selection, and overfitting should be explicitly tackled by the estimation methodology, to create an AI system that is balanced between accuracy and explainability. The PhD candidate will become a member of a young research team and will have the opportunity to collaborate with a number of biomedical partners across the planet.
he PhD position is funded by EAISI (Eindhoven Institute of Artificial Intelligence Systems), so that collaboration will also involve AI researchers of the Institute in various disciplines.
You, as a successful applicant, will perform the research project outlined above in an international research team. You will report research findings at international conferences and workshops, and in high-quality scientific journals. The research will be concluded with a Ph.D. thesis. A small teaching load (on average about 10%) is part of the job description.
he project will be supervised by Dr. Marco S. Nobile.
Do you recognize yourself in this profile and would you like to know more? Please contact Marco S. Nobile, hiring manager, m.s.nobile[at]tue.nl. For information about terms of employment, please contact Susan Opgenoorth, HR advisor, hrservices.ieis[at]tue.nl or +31 40 247 8827. Are you inspired to know more about working at TU/e? Please visit www.tue.nl/jobs.
Your application must contain the following documents (all in English):