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Field
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skills and experience with tools such as MATLAB or Python Life cycle assessment (LCA) Software related experience on system dynamics modelling, GIS, and energy simulations Research writing and publications
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protocols such as TCP/IP. Familiarity with interpreted scripting languages such as Python or Bash. Knowledge of database concepts and/or familiarity with SQL. Exposure to geospatial analysis and GIS concepts
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | 3 months ago
software commonly used in research, such as Python, MATLAB, R, or GIS tools. Excellent written and oral communication skills to effectively convey research findings to diverse audiences, including students
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(past experience with interdisciplinary research is a plus), in particular focusing on hazard, risk and disaster risk reduction GIS qualifications are of major advances Excellent command of English, both
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familiar with spatial analyses, species distribution modelling (SDM), and programming in the R or Python languages to apply these to: Collate and analyse spatial data on MPA boundaries, their protection
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, tracking, spatio-temporal modeling, edge learning) using field data (traffic cameras, micromobility telemetry, connected vehicle/V2X, crash records, GIS). · Manage and coordinate pilot deployments
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of dendrochronology techniques, from the research plan, field work and laboratory, and interpretation and publication. He/she should be comfortable with the R and/or Python languages. Experience in handling large
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integration, database systems, or data quality. 2. Skills: Proficiency in Python (data processing, APIs) and good engineering practices (Git, testing, documentation). Experience with at least one: vector search
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analysis, GIS and Python regarding urban and regional planning Documented experience of working with urban and regional policies and qualitative data. Documented experience of working with transport related
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integration, database systems, or data quality. 2. Skills: Proficiency in Python (data processing, APIs) and good engineering practices (Git, testing, documentation). Experience with at least one: vector search