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clinical approaches, including: Histopathology and digital pathology (whole-slide imaging, WSI) Quantitative analysis of the tumour immune microenvironment AI-based image analysis, machine learning and deep
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DEVCOM Analysis Center. Topics of particular interest include: 1. Development of novel machine learning and AI models, as well as the adaptation of existing approaches for AI-enabled decision aid systems
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, statistical analysis, and mathematical modelling. Provides support for use of developed methods. Remains up to date on the scientific literature of statistical methods and machine learning as applied
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, Mechanical), Computer Science, Applied Math/Statistics, Physics—or related. Candidates who will graduate in the near future are also welcome to apply. Strong foundation in machine learning/deep learning and
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 21 days ago
the machine learning community as challenging, high-dimensional testbeds. Notably, the recently developed WOFOSTGym simulator \cite{solow2025wofostgym}, bridging crop modeling and RL, received the Outstanding
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. Integrate physical laws, experimental data, and simulation results into unified machine learning frameworks to improve model robustness and generalizability. Conduct data preprocessing, model training, and
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Description Completion of doctoral thesis related to: Process and analyze experimental data. Develop predictive models using deep learning. Train, validate, and optimize neural networks (CNNs, etc.) applied
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on Graphs: Symmetry Meets Structure (LOGSMS). The field of Machine Learning on Graphs aims to extract knowledge from graph-structured and network data through powerful machine learning models. Designing
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Lab applies rigorous evaluation and modeling methods, including natural and field experiments, randomized controlled trials, behavioral economics, and machine learning, to help policymakers identify and
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, or a related field. Proven experience in machine learning, deep learning, generative AI and data mining. Strong programming skills (e.g., Python, R, MATLAB, or similar). Experience with data