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Field
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investigate new algorithmic principles that make learning agents adapt to non-stationary environments in an autonomous manner. The expected outcomes are new theoretical insights about the algorithmic roots
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(quantitative, qualitative, modelling, GIS, etc.). Produce and share research outputs such as: articles and preprints, demonstrators or prototypes, documented datasets and, where possible, open data, a scientific
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and Stata. Working with large datasets, including merging files into the data archive. Creating clear data visualizations to communicate results (including GIS maps). Assisting with the preparation
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-agents for perception and communication. Candidates ideally have a background in computer science, electrical engineering, or related fields, and a strong interest in machine learning, optimization
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escrita en español e inglés - Experience in analysing traffic accident data and road safety - Advanced knowledge of spatial analysis and Geographic Information Systems (GIS). - Proficiency in statistical
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/PhD) or related field. - Simulation & data: TRNSYS (or similar), time-series processing; Python (pandas/numpy). - Experience with GIS and/or climate/solar datasets (e.g., METEONORM, PVGIS
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, Biomedical Sciences, Bioengineering, or related fields. Enthusiasm for fundamental science and attention to detail. Motivation to work with an international team of PhD students, postdocs and technicians
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objectives (e.g. geography, biology, epidemiology and public health). The person recruited will have competence in statistical analysis and GIS, experience or at least interest in carrying out field work and
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of Warsaw. Laboratory: Biomolecular Machines Laboratory Project leader: Dr Monika Wojciechowska Project title: Development of new antibacterial agents based on lytic enzymes produced by bacteriophages
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industry. Responsibilities and qualifications Your overall focus will be to advance the development of a sustainable photochemical reduction process for PFAS mineralization using a green reducing agent. You