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(R2) Positions PhD Positions Country Portugal Application Deadline 8 Sep 2025 - 23:59 (Europe/Lisbon) Type of Contract Temporary Job Status Full-time Offer Starting Date 1 Oct 2025 Is the job funded
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external research efforts, including partnerships with industry. Key responsibilities include: • Supporting the setup and ongoing management of histology facilities, including paraffin and cryo
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discovery through integrative approaches. Time-series and longitudinal multi-omics data analysis for disease progression modeling. Explainability and interpretability of AI models to support clinical decision
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Python, R, or MATLAB. Solid understanding of battery systems, electrochemical processes, or energy management. Preferred Skills: Experience with time-series analysis, predictive modeling, and anomaly
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references. Please upload those in PDF format to the Applicant Document section as Specific Request 1. Skills / Knowledge / Abilities Knowledge: Seismology, geophysics, time-series analysis, and appropriate
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these various goals whilst future climatic changes are projected to progress most rapidly in the boreal region, will require adaptive management strategies. For this purpose, a transformation from traditional
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 2 hours ago
gregor.b.steinbruegge@jpl.nasa.gov (818) 393-7913 Applications with citizens from Designated Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of
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Application Deadline 14 Sep 2025 - 22:00 (UTC) Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 1114
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open until the position is filled. Applications consist of a curriculum vitae, publication list and a description of past research and future interests (maximum of 3 pages including figures and
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architectures, attention mechanisms, and fine tuning techniques for LLMs. Experience with time-series data, anomaly detection, or predictive maintenance is a strong plus. Familiarity with industrial datasets and