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Field
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of the correctness of software and hardware systems using machine learning. Recent advances in neural certificates—such as neural model checking and neural termination analysis—have shown promising results in
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of classes, using Machine Learning (ML) techniques such as Decision Trees, K-Nearest Neighbors (KNN), XGBoost, Support Vector Machines (SVM), or Neural Networks. Explore and implement clustering algorithms
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expertise in the following areas: Machine Learning in general, with an emphasis on deep learning and language modeling Model benchmarking and evaluation pipelines for NLP/LLMs Domain-aware application of AI
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scientific conferences and publish models and scientific insights in high-impact journals Who You Are: Ph.D. in Computational Biology, Bioinformatics, Computer Science or Machine Learning related field
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developing statistical and machine learning approaches for the integration of cancer multi-omics data and the analysis of CRISPR-based screens. Responsibilities include designing bioinformatics workflows
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 10 days ago
data sharing (preferred); good knowledge of machine learning algorithms; proficiency in high-level programming languages (e.g., C++, Python, C#, etc.) (preferred); knowledge of database formulation and
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Research Fellow in AI for Healthcare (1 FTE) – ArcHub ICUSafeNotes-School of Computer Science 011287
breakthroughs into commercial healthcare solutions. In the ICUSafeNotes project, we are conducting research and development of multimodal machine learning models that includes ICU note summarisation and analysis
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, control theory, data science, data driven methods, discrete mathematics, graph algorithms, high-performance computing, integral equations and nonlocal models, linear and multilinear algebra, machine
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plan: The work consists of developing models for the prediction of biological control agents (BCAs), using different approaches: Machine Learning (random forests, support vector machines, lasso), Deep
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machine learning and statistical analyses. Proficiency with Python and relevant libraries. Prior experience with genomic data modeling. Interest or experience working in neuroscience domain applications