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Field
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knowledge of electrochemistry and experience with fuel cell test Ability to cooperate across disciplines in an international environment Independent, structured and target oriented way of working Software
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: Master’s degree in computer science, computer/software engineering, applied mathematics, artificial intelligence, or a related field. Strong skills in deep learning (e.g., PyTorch/TensorFlow). Experience in
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software, polymer technology Additional Information Work Location(s) Number of offers available1Company/InstituteTallinn University of TechnologyCountryEstoniaGeofield Contact State/Province Harjumaa City
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mathematics. The applicant should be skilled at implementing new models and algorithms in a suitable software environment, with documented experience. Experience in applying or developing machine learning
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novel methodology and software to assess the resilience of major hazard plants under NaTech multi-hazard scenarios. The approach includes defining tailored resilience indicators, formulating a
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integrating single-molecule fluorescence detection and microfluidics Implementation of data acquisition and analysis software (programming) Methodological innovation and biological applications Who Should Apply
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in a suitable software environment, with documented experience. Experience in applying or developing machine learning models for atomistic systems (in chemistry or physics) is advantageous
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Master’s degree (120 ECTS), with experience in Animal Breeding. Experience with data handling softwares (e.g., R, SAS, Python, Unix Shell) and genetic softwares (e.g., DMU, F90, AIREML). Background in
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and computational workflows for chemical exposomics and metabolomics, with a strong emphasis on creating and maintaining open-source software and training resources. Scientific Context Humans
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working with complex systems and troubleshooting. Proficiency in specialized instrumentation and data analysis, including the use of relevant software, is highly desirable. Strong analytical skills and the