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Engineering » Mechanical engineering Researcher Profile Recognised Researcher (R2) Positions PhD Positions Application Deadline 2 Oct 2026 - 00:00 (Europe/Brussels) Country Poland Type of Contract Permanent Job
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neutron stars. However, reliable predictions in regions where experimental data are scarce remain limited by uncertainties in model parameters, functional form, and the extrapolation of calibrated
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predict the behavior. You will be embedded in our team, which holds dedicated in-house expertise in 3D printing, pH-feedback systems and modeling, and you will have assistance on the various aspects
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PatchSentinel-X: Transformer-Based Security Patch Intelligence for Vulnerability Lifecycle Assurance
Please note that this PhD topic is offered exclusively at our Monash Malaysia campus and is not available at the Clayton campus. Core PhD Question Can Transformer models understand the full
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engineering) Causal inference / uplift modeling / synthetic controls Modern ML frameworks: LightGBM/XGBoost, CatBoost, PyTorch,JAX, TensorFlow) LLMs / agentic workflows (LangChain/LlamaIndex/Haystack
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modeling, or real-time data analysis. Familiarity with data visualization, reproducible research workflows, version control, and collaborative coding practices. Interest in translating computational methods
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Framatome's Research Center (DTI). **PhD Programme** The objective of this PhD research is to develop a wear model capable of predicting wear kinetics under variable impact-fretting loading conditions for a
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Explore trace element thermodynamics in high-temperature systems to control steel quality in the green transition—a PhD bridging experiments, modelling, and industrial impact. Job description The
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learning, understand their mathematical foundations, and connect them to space-related technologies and missions. The focus is on building rigorous models that explain and predict the behaviour of modern
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of experimental and/or simulation data, the development of predictive models linking cellular responses to the properties of the surrounding environment, and the implementation of explainable AI approaches