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Field
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advantage but not mandatory. Experience with relevant neuroimaging software, secure research infrastructures (e.g., SAFE or HPC), and experimental platforms such as PsychoPy is also considered an advantage
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of software infrastructure to optimize data workflows Developing analytical methods to integrate different types of sequencing-based DNA data. Developing computational models for prognosis and treatment
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, including a mixture of classical and quantum mechanics simulations, cheminformatics and machine learning, as well as collaborative software development, providing expertise for a broad range of future careers
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acquisition. Ability to analyse and interpret experimental data. Experience using MATLAB, Python or equivalent software for data analysis. Strong technical problem-solving skills and the ability
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quantitative and/or qualitative research methods and be willing to further develop expertise in advanced methodologies. Experience with survey research, content analysis, statistical software (e.g., R, SPSS
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computer, virtual data storage, and access to software tools for specialized data analysis (e.g., Cryo-EM data, crystallography, etc.). Structural microbiology: Exopolysaccharide secretion and host
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, and a Continuum+K3 GIF. The group will also further data analysis using and developing software routines for analysis of large datasets. Research projects span beam-sensitive materials with
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(Findable, Accessible, Interoperable and Reusable) data principles and using tools such as Git and software containers to support reproducible and robust data analysis. Applicants should hold a degree (BSc
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of the software and its configurations. This project will investigate novel techniques for the application of formal methods to the design, verification, and validation of embedded systems, with particular emphasis
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selection criteria High skills in applied mathematics, problem mathematicalising and solving Practical experiences with networked systems and multi-vendor softwarized environments Experience with 5G radio