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Field
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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responsibilities will include: Pre-registering data analysis plans; Leading and conducting advanced statistical analyses (e.g., twin/family designs, genomic and epidemiological methods, longitudinal modelling
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knowledge of methods and theories Experience or willingness to engage in academic teaching Very good English skills and, if possible, German skills or another foreign language What we offer: Work-life balance
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interpretability, explainability, and verification methods with an emphasis on white box methods and control techniques using causality. The post holder will work on projects that bridge technical AI capabilities
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for chronic fuel cell monitoring in vivo including common electrochemical characterization methods. • Design and manufacture an micromachined interface between the fuel cell and the implantable
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ultimately contributing to the development of new antiviral approaches. The project takes a cross-disciplinary approach, combining biochemical, biophysical, cell biological, and virological methods, including
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for chronic fuel cell monitoring in vivo including common electrochemical characterization methods. • Design and manufacture an micromachined interface between the fuel cell and the implantable instrumentation
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modelling to study the causes and consequences of extreme chromosomal instability in these cancers. The role will involve: - Learning and applying cytogenetic methods for generation and analysis of chromosome
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the mindfulness intervention Analysis of quantitative and qualitative data generated from the project Compiling a report to the funding body at the half way and end of the project Preparing a mixed methods article
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Devices." The project focuses on cutting-edge research into the growth, characterisation, and application of high-performance two-dimensional (2D) materials using metal-organic chemical vapour deposition