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using Python. Analyzing both quantitative and qualitative data including methodologies such as multiple regression, thematic analysis and text mining. Transcribing and coding qualitative data using
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Python/Java/C++ be proficient in written and spoken English be able to work in a team We offer: Working in a team of enthusiastic scientists who work to push the boundaries of knowledge in the field in
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, or related fields. Strong programming skills in Python. 0–3 years of relevant experience. Experience building data processing pipelines (ingestion, cleaning, transformation, feature extraction, evaluation
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doctoral thesis agreement, including an application to one of the Universit of Vienna doctoral schools (e.g., CoBeNe, https://vds-cobene.univie.ac.at/) within 12–18 months. As a University Assistant
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. Scripting in Python, Bash, or Go. Familiarity with TCP/IP, DNS, firewalls, and load balancing. Solid grasp of application security best practices. Strong problem solving in complex, multi-tier environments
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on the lab and project needs. There may be work that is required outside of normal hours for sample collection. Minimum Qualifications Full Employment Eligibility Requirements can be found here: https
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reviews to guide experiment design and identifying emerging methodologies. Processing and analyzing large experimental datasets using scientific computing tools (Python/Matlab). Maintaining laboratory
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ineligible for visa sponsorship. This is a hybrid position requiring at least 3 days per week onsite. Responsibilities Develop and maintain web applications using technologies such as Python, JavaScript, HTML
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. Knowledge of geoinformation technologies, 3D building modelling (BIM), and AI applications Knowledge of R and Python—especially spatial data science techniques Analytical and process-oriented thinking as
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combining qualitative and quantitative analysis Familiarity with R, Python, or similar analytical tools. Experience with text analysis and survey methodology Knowledge of energy, climate, or sustainability