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techniques, tools, and systems, by which scientists may solve problems affecting various aspects of human life. We believe that to advance the state-of-the-art and create meaningful computational solutions
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industry partners to advance the lab's research goals. Qualifications: A Ph.D. in Computer Science, Engineering, or a related discipline, with a focus on security, privacy, or applied machine learning, and
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PhD Positions Application Deadline 8 Aug 2026 - 23:59 (Europe/Warsaw) Country Poland Type of Contract Temporary Job Status Full-time Hours Per Week 40 Offer Starting Date 14 Aug 2026 Is the job funded
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) Application Deadline 26 Jul 2026 - 00:00 (UTC) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU
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) Application Deadline 3 Aug 2026 - 21:59 (UTC) Country Czech Republic Type of Contract Temporary Job Status Part-time Offer Starting Date 1 Jan 2027 Is the job funded through the EU Research Framework Programme
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position of which they have applied. For general application assistance or if you have questions about a job posting, please contact Human Resources at 479.575.5351. Department: Post Docs, GAs and Hourly
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, Number Theory, Representation Theory, Topology, and Probability. The department has a thriving Ph.D. program that attracts students from across the globe and offers positions with close faculty interaction
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research results in high-impact scientific journals. Your profile We are searching for a highly motivated candidate who has: A PhD in natural sciences, e.g. geology, soil science, microbial ecology
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discussion and analysis. They will interact extensively with the PI, graduate and undergraduate students and other postdocs in the group. Job duties 35% experiment design and execution 35% research 30
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of the following: computational analysis of human movement and/or vocalization, time series analysis, pattern finding, statistical modelling, audio feature extraction, music information retrieval, machine learning