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learning and statistics Apply for this job See advertisement About the position We invite applications for a three-year PhD Research Fellowship in probabilistic machine learning and statistics at the
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many animals of a given species are present at a certain location and time. This interdisciplinary PhD aims to close that gap by combining recent advances in acoustic individual identification (AIID
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many animals of a given species are present at a certain location and time. This interdisciplinary PhD aims to close that gap by combining recent advances in acoustic individual identification (AIID
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hydroclimatic and socioeconomic forcing. https://eurosoho.eu/ FUTURA coordinates European modelling and infrastructure efforts to jointly develop and deploy a sustainable, aligned system for delivering future
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spatial statistics. Close the experimental-computational loop, using analysis results to guide the design of the next round of automated experiments (design of experiments, active learning). Ensure
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Application process Please submit your complete application via https://jobs.liser.lu/jobs including: a detailed CV ; a cover letter outlining your interest, motivation and suitability for the PhD
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, R) and geospatial tools (e.g., ArcGIS, QGIS ), spatial statistics, or cloud computing Experience working in collaborative research teams Valid driver’s license and be able to successfully pass a
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: Continuous recruitment until position filled; application review to begin on September 11, 2026 Salary Information: Step 18 ($32,784 annual, MA Program); Step 19 ($34,098 annual, PhD Program at 50% FTE
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Memorial Sloan Kettering Cancer Center | New York City, New York | United States | about 11 hours ago
biostatistics, statistics, computer science, computational biology, or related quantitative discipline. Have published a 1st author paper from PhD dissertation or postdoctoral research Core Skills
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Mathjobs.org | 25 days ago
[IMAGE] Postdoctoral Associate Required Qualifications: (as evidenced by an attached resume) ● PhD (or foreign equivalent) in Applied Mathematics, Physics, Theoretical/Computational Biology