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-constrained inference, time series, and Bayesian analysis. In applied mathematics, these include information theory, coding theory, control theory, fluid mechanics, and mathematical biology. Further
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Pontificia Universidad Católica de Chile | 2 months ago
(CLASS), VLT Multi-Object Optical and Near-infrared Spectrograph (VLT-MOONS), 4-m Multi-Object Spectroscopic Telescope (4MOST), Fibre Dual Echelle Optical Spectrograph (FIDEOS), TAO-AIUC high-Resolution Y
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monitoring, and the design of manipulation experiments, development of diagnosis frameworks (e.g., knowledge-guided machine learning, casual inference, and Bayesian neural networks), evaluation of
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biological and medical research questions. Strong expertise in (Bayesian) statistics and data science Experience with mathematical modelling (e.g., linear algebra, linear models methodologies
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manufacturing environments, particularly pick-and-place operations, remains challenging when parts and environmental conditions vary. Conventional robotic systems rely on fixed object categories and
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, Computer Science, Data Science, or related field • Experience in point cloud analysis or real-time object tracking • Proficiency in programming and data-driven design workflows • Experience in
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environmental sciences. Evidence of engagement with climate-related research as well as Bayesian econometric methods is desirable. The post is available for 60 months starting March 1, 2027, or as soon as
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areas might include, but are not limited to, spatio-temporal models, time-series analysis, anomaly and change-point detection, Bayesian hierarchical models, statistical machine learning, optimal
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support the design, development, and independent evaluation of multi-source data fusion, environmental modeling, and digital twin / multi-agent simulation capabilities, including object detection
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as grasping, object reorientation, bimanual manipulation, and assembly Advance techniques including behavior cloning, reinforcement learning, and VLA-based reasoning, with a focus on novel