AI-assisted metadata harmonisation for mouse models of human disease

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Glasgow, United Kingdom

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Closes: Jun 5, 2026

Utilizing machine learning to decipher the mechanism of protein-DNA binding

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Manchester, United Kingdom

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Enhancing metabolomics data repository re-use through enhanced metabolite annotation and data harmonisation

University of Liverpool

Liverpool L69 3BX, UK

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Transcriptional Noise as a Biomarker of Healthy Ageing: A Genome Informatics Approach

University of Salford

43 Crescent, Salford M5 4WT, UK

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Leveraging sequencing technologies to advance identification of bacterial pathogens

University of Liverpool

Liverpool L69 3BX, UK

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Bioinformatic analysis of the function of mRNA poly(A) tails

The University of Nottingham

Nottingham NG7 2RD, UK

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Biologically-informed machine learning to identify clinically actionable subgroups in bladder cancer

University of York

Heslington, York YO10 5DD, UK

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Advancing Untargeted Metabolomics through a Probabilistic and Context-Aware Annotation Pipeline

University of Liverpool

Liverpool L69 3BX, UK

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Bioinformatics analyses of microbial communities and their genetic contents to understand the transmission dynamics and selection of antimicrobial resistance

University of Reading

Whiteknights House, Reading RG6 6UR, UK

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Bioinformatics studies of protein structures, functions and their interactions

University of Reading

Whiteknights House, Reading RG6 6UR, UK

Student / Phd Jobs

Algorithms and methodology for understanding bacterial plasmid evolution (HUBERK_U26CMP)

University of East Anglia

Research Park, Norwich NR4 7TJ, UK

Student / Phd Jobs

Utilizing machine learning to decipher the mechanism of protein-DNA binding

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Manchester, United Kingdom

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AI-assisted metadata harmonisation for mouse models of human disease

Utilizing machine learning to decipher the mechanism of protein-DNA binding

Enhancing metabolomics data repository re-use through enhanced metabolite annotation and data harmonisation

Transcriptional Noise as a Biomarker of Healthy Ageing: A Genome Informatics Approach

Leveraging sequencing technologies to advance identification of bacterial pathogens

Bioinformatic analysis of the function of mRNA poly(A) tails

Biologically-informed machine learning to identify clinically actionable subgroups in bladder cancer

Advancing Untargeted Metabolomics through a Probabilistic and Context-Aware Annotation Pipeline

Bioinformatics analyses of microbial communities and their genetic contents to understand the transmission dynamics and selection of antimicrobial resistance

Bioinformatics studies of protein structures, functions and their interactions

Algorithms and methodology for understanding bacterial plasmid evolution (HUBERK_U26CMP)