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Field
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focus on combining simulations using spatial-genetic-demographic individual based models (e.g., using the software SLiM), machine learning approaches, and genomic data to estimate larval dispersal
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be supervised by Carla Groenland. You will have the opportunity to collaborate with postdocs, PhD candidates, and other faculty members of the research group in Discrete Mathematics and Optimization
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can you 3-colour an n-vertex graph of diameter 2?'). The PhD will be supervised by Carla Groenland. You will have the opportunity to collaborate with postdocs, PhD candidates, and other faculty members
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related field with a strong quantitative focus. Strong programming skills in Python and demonstrated experience with machine deep learning frameworks (for instance, PyTorch or TensorFlow), preferably
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, or computer science. Core competencies: solid background in quantum many-body physics strong programming skills (Python required, Rust a plus) experience with tensor networks, variational Monte-Carlo, machine learning
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in laboratory work and materials characterization techniques (e.g. SEM, ICP-MS) Basic knowledge of thermodynamic modelling or willingness to learn tools such as FACTSage Analytical mindset with strong
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complex contexts through statistical models, machine learning (ML) methods, and artificial intelligence (AI). This includes working with performance, scalability, resilience regarding platform architectures
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mechanisms that integrate queueing theory, traffic modelling, machine learning, and network-performance prediction for improving latency, reliability and fairness to support mission‑critical services
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, or supervised/unsupervised learning depending on the available data) using spatial analysis and geographic machine learning tools (e.g., scikit-learn, PyTorch/TF + GeoPandas/Shapely) - Implementing a semantic
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» Maritime engineering Engineering » Computer engineering Computer science Architecture » Naval architecture Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 23 Aug