9 genetic-algorithm Fellowship positions at University of Birmingham in United Kingdom
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-edge research in machine learning and automated reasoning for safe algorithmic systems. The Research Fellow will be responsible for developing advanced theory and machine learning algorithms
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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be ideally be proficient with microbial genetics, molecular microbiology, basic tissue culture and molecular biology techniques. Prior experience with bioinformatics (microbial sequencing and
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using multicolour flow cytometry to analyse immune responses Experience of molecular cloning techniques and working within genetically modified organism risk assessments Holder of Home Office Personal
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the origin of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks
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genetic events with PRMT5 inhibitors in Ewing sarcoma, focusing on the DNA damage response and splicing. We require a highly motivated and organised individual that is willing to meet deadlines. Principal