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Field
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We are seeking to appoint a well-trained, enthusiastic and self-motivated scientist to join our team to investigate the mechanisms underlying the function of non-canonical RNA/DNA structures (R
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Join the University of East London – Shaping Futures for 125 Years University of East London (UEL) is a vibrant, diverse, and forward-thinking institution dedicated to transforming lives through exceptional education and career-focused opportunities. As a careers-first university, we have been...
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) aims to strengthen its industrial partnerships within and beyond Morocco and Africa by adopting an integrated and sustainable strategic vision of R&D and training. The institute focuses on various
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R and Python and be highly proficient in using R for statistical analysis, bioinformatics, data visualization, and multi-omics data analysis. The candidate should be comfortable independently
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Establish MS-based biomarkers for target engagement and clinical studies Analyse datasets in Python/R; publish and mentor students What we offer Ownership of the LRRK2 workstream within a major international
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sampling; selection, acquiring, reformatting, and sampling gridded environmental data for use as model covariates; creating species density surface models, typically in R with mgcv-based generalized additive
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multimodal data analysis is preferred; experience with R, machine learning, or advanced statistics is a plus. Training and Research Environment: The successful candidate will receive interdisciplinary training
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their PhD within the last 2 years at the time of application. Expertise Hands-on expertise in circular RNA (circRNA) biology — validation (divergent RT-PCR, RNase R resistance, back-splice junction sequencing
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data analysis (e.g., MRI, EKG) and programming (e.g., Python, MATLAB, R). Expertise in machine learning, deep learning, foundation models/LLM. Excellent quantitative and analytical skills. Strong written
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to characterize the brain network interactions using connectivity and graph theory metrics. Develop reproducible computational pipelines in MATLAB, Python, R, or similar platforms for electrophysiology processing