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Biologically-informed machine learning to identify c: 663661

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

Applications Close: Jul 7, 2026

University of York

Heslington, York YO10 5DD, UK

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663661

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University of York

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

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13 Jobs Found

Development of AI framework for iPSC image analysis and integration with transcriptomics

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

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

University of York

Heslington, York YO10 5DD, UK

Student / Phd Jobs

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

University of Liverpool

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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

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Student / Phd Jobs

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

Closes: Jul 27, 2026

Closes: Jul 27, 2026

Closes: Jul 13, 2026

Closes: Jul 8, 2026

Closes: Jul 7, 2026

Closes: Jul 7, 2026

Closes: Jul 7, 2026

Closes: Jul 7, 2026

Closes: Jul 7, 2026

Closes: Jul 7, 2026

Closes: Jul 7, 2026

Closes: Jul 6, 2026