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- Delft University of Technology (TU Delft); yesterday published
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- Delft University of Technology (TU Delft); Published yesterday
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- Delft University of Technology (TU Delft); 16 Oct ’25 published
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- Delft University of Technology (TU Delft); 26 Sep ’25 published
- Delft University of Technology (TU Delft); Published today
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- Eindhoven University of Technology (TU/e); 10 Oct ’25 published
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- Eindhoven University of Technology (TU/e); Published 7 Nov ’25
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- Erasmus MC (University Medical Center Rotterdam); Published yesterday
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- Leiden University; Published today
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- Maastricht University (UM); yesterday published
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- University Medical Centre Groningen (UMCG); today published
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- Wageningen University & Research; today published
- Wageningen University & Research; yesterday published
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Field
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contaminants. Your part within this larger European project, will be to design and optimize the air filtration unit for the fuel cell system. For this, you will perform a detailed modelling study, complimented
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that can self-learn bulk visco-elastic properties? How to structure such materials to learn continually and counteract the aging of their own parts? Can we optimize self-learning materials to achieve
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through optimization of ion channels incorporation and activity in lipid bilayers. The project sits at the interface of biophysics, engineering and biochemistry. The PhD student will be part of
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in the field of hybrid dynamical systems, observer design, learning techniques, and optimization. Knowledge of at least one programming language: Matlab, Python, is expected. Eager to work within a
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optimal deployment of department staff. Driving the professional development of the field, the department, and its employees. Taking final responsibility for executing diagnostic tests under ISO17025
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Network (FSDN), we work with a data management platform for data collection and modelling. Our management team needs additional expertise to better map out processes and data models and to optimize
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-up. In the ZonMW-funded AI for EVAR project, we develop multi-modal models for optimized selection of treatment before, and follow-up after EVAR. You will implement and advance multimodal deep learning
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, including EEG. You will design and optimize experimental tasks, collect and analyze behavioral and neural data, and adapt computational models to capture variability between individuals. What you will be
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methodologies; You will characterise the materials using spectroscopic and surface characterisation techniques; You will identify and implement optimal methods for the integration and testing of materials in real
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presence across various platforms. You are both analytical and hands-on: you evaluate our social media performance, identify trends and optimize our campaigns, while also creating messages in a (visually