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Field
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data (transcriptomics, proteomics and metabolomics), from a large collection of well-characterized samples to identify novel biomarker and causal and druggable targets. We are seeking a motivated
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for more information. About you To be successful in this role, we are looking for candidates to have the following skills and experience: Essential criteria 1. PhD degree in Engineering, Computer
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neuro-adaptability with changes in cortical manifestations during an intervention (e.g., non-invasive brain stimulation) for symptom reduction. Large-scale data analysis (e.g. machine-learning) will
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(Python, MATLAB) for processing and analyzing large or multimodal datasets (e.g., neural activity and behavior). Experience working with quantitative behavioral or electrophysiological data collection
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complements LCAB’s research programmes. High competence in the analysis of large ecological and other data sets and time series. Ability to write up research for publication in high profile journals, along with
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qualification in Genetics, Bioinformatics, Computer science, Data science, Statistical Genomics or a related discipline involving the interrogation of ‘omics’ datasets. Hands-on experience with large-scale human
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that connect animal health, data analysis, and human behavior. Design and carry out field studies, collecting and analyzing large data sets. Use and evaluate AI tools to support research and training. Create
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secure food system. You also possess: a PhD in Biology, Biotechnology, Bioengineering, Biochemical Engineering, or related fields, with demonstrated experience in animal cell culture; minimum of 2 years
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combine large-scale data, computational methods, and clearly articulated social-science theories to improve our understanding of society. Recent advances in machine learning, natural language processing
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experience in life cycle assessment (LCA) and related tools for managing large data sets to evaluate natural resources needed to advance emerging technologies. The candidate will lead their primary project and