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computational tools such as Python or MATLAB Excellent team player that can also work independently High degree of reliability, organizational and interpersonal skills Service oriented approach towards researches
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skills with proficiency in Python, TensorFlow/PyTorch, and experience with containerized deployments and MLOps practices. Data Pipeline Engineering: Extensive experience with end-to-end data pipelines
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biology, or other laboratory-based insect research Quantitative data analysis, including experimental design, statistics, and use of R, Python, or similar tools for biological data analysis Special
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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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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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. 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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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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Expertise in FEM software (ABAQUS, ANSYS, SAP2000) and coding (Python/MATLAB). Professional engineering licensure (HKIE/CEng) or eligibility is a plus. Candidates for Professor or above should have
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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