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analysis Large language models or machine learning/predictive modeling for longitudinal data analysis Strong computer programming skills Strong mathematical or statistical skills Ability to work as a part of
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
their impact on the tumor immune microenvironment and immunotherapy response. 3) Developing clinical-grade mechanism-driven AI models (iGenSig-AI) for predicting responses to targeted therapies and
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leading international centre for developing computational models that support personalised, efficient, and predictive healthcare—advancing the future of medicine through digital transformation. More info
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scientific data, model architectures, and training dynamics influence scientific predictions. You will join a vibrant research environment at TU/e at the intersection of AI, scientific computing, and
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, mathematics, computer science, engineering or a related discipline Required Other None Additional Preferred Experience working in one of the following areas: Machine learning/predictive modeling
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predictive confidence, including sensitivity and identifiability analyses Compare grey-box models against purely mechanistic and purely data-driven approaches Optimize model performance for computational
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stability prediction Collaborating closely with experimental researchers for iterative model refinement Publishing high-impact research at the intersection of AI and molecular design Supervising students
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background in nonlinear optics, ultrafast photonics, and integrated photonics, alongside the ability to develop predictive models for optical materials and photonic devices. The successful candidate will work
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prediction, and world models. Along with industrial and government partners, the postholder and project team will use these methods to address current issues with LLMs, such as reward hacking, active learning
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. The Postdoctoral Associate will work under the direction of the Principal Investigator in building a first-of-its-kind Software as a Medical Device (SaMD) that predicts, detects, and manages SSIs by fusing RGB