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be made for special reasons). Experience in research on digital cultures. Proficiency in AI methods (e.g., NLP techniques, machine learning, and large language models, LLMs)—including web scraping
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) Corrosion behavior (electrochemistry & high-temperature oxidation) In-situ monitoring of AM processes Computational skills in: Phase-field modeling, Machine Learning, FEM, DEM, COMSOL Alloy design (CALPHAD
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Location: Cambridge, Massachusetts 02142, United States of America [map ] Subject Areas: Artificial Intelligence Biology Machine Learning Appl Deadline: (posted 2025/09/30, listed until 2026/03/30) Position
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that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service or similar circumstances, as well as clinical
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), research is carried out in computer vision, robotics and machine learning. We are now looking for two postdocs in robotics and machine learning and computer vision. The successful candidates is expected
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of data at high luminosity (after Upgrade-2), participation in coordination of activities in software groups or data analysis groups, coaching of PhD as an auxiliary supervisor on machiner learning, new
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opportunity for someone who thrives in an interesting and challenging work environment. Core responsibilities include: Research in the intersection of discrete optimization and machine learning, including
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intelligence, machine learning, data science, applied mathematics, or a closely related field, awarded no more than three years prior to the application deadline*. Documented research experience in machine
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., knowledge representation and reasoning) and bottom-up (e.g., machine learning) methods to study the representation of geographic categories and processes. While we welcome applicants from a broad range of
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-preserving finite element methods, advanced solver strategies, multi-fluid systems, surrogate modeling, machine learning, and uncertainty quantification. The position comes with a travel allowance and access