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of Assistant Teaching Professor in Spatial Data Science. The successful candidate will teach and advise students in Penn State’s online geospatial education programs: https://geospatial.psu.edu . This is a 36
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Location: Singapore, Singapore 259569, Singapore Subject Area: Sociology / Applied Research Methods, Mixed Methods, Statistics, and Data Analysis Appl Deadline: 2026/01/17 00:00AM (posted 2025/12/22
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methods for single-cell data analysis (tools developed by the team : https://github.com/cantinilab ). Single-cell high-throughput sequencing, extracting huge amounts molecular data from a cell, is creating
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: Initial appointment is 1 year with the expected renewal after the first year for an additional 1-2 years by mutual agreement. Appointment Start Date: Flexible Start Date Group or Departmental Website: https
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) Recognised Researcher (R2) Positions PhD Positions Country France Application Deadline 3 Feb 2026 - 12:00 (Europe/Paris) Type of Contract Temporary Job Status Full-time Offer Starting Date 2 Mar 2026 Is the
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these skills. Competence in data processing, statistical analysis, and the development of ML models, or a clear willingness to gain such expertise. Experience with GIS-based spatial analysis, or a clear
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for Research Staff Development for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD in spatial
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. We welcome applicants with a PhD (or equivalent) in biostatistics, statistics, or a closely related quantitative field. We seek scholars with training in biostatistics/statistics and demonstrated
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more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Development of statistical methods for estimating plant population size and change Mathematical
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FieldPhysicsYears of Research ExperienceNone Additional Information Eligibility criteria - A PhD in mathematics/statistics/AI applied to ecological issues. - A strong publication record. - Proficiency in R and Python