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Field
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publications Assist in supervising research students in the group Job Requirements: PhD degree in microbiology, bioinformatics, computational biology or a related field. Expertise in python, linux and HPC. Have
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students in the group Job Requirements: PhD degree in microbiology, bioinformatics, computational biology or a related field. Expertise in python, linux and HPC. Have experience in conducting wet-lab
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manipulating omics datasets, including spatial transcriptomics, RNA-seq, and single-cell RNA-seq. Familiar with high-performance computing (HPC) environment and possesses good computational biology skills
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environments such as HPC clusters. Familiarity with PEST, model calibration and uncertainty analysis is advantageous. Is able to work independently and take initiative when opportunities arise while also
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-consuming minerals. Passivation and secondary mineral formation and their effects on permeability. Has experience with modern high-performance computing environments such as HPC clusters. Familiarity with
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experience in computational biology or cancer genomics Experience with high-performance or cloud computing (e.g., HPC, AWS, GCP) At least one first-author peer-reviewed publication Strong communication and
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, teaching, and student engagement in AI-for-Science courses and seminars. - Support the development and deployment of AI-driven tools for High-Performance Computing (HPC) applications. Qualifications
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, as is experience of working with HPC. Excellent data organising skills, oral and written communications skills, problem-solving abilities and time management skills are also a requirement. Experience
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postdoctoral position within the Q-VERSE EU project, which aims to provide a ready-to-use quantum software toolkit that supports various APIs and HPC interfaces in an open and transparent manner for Europe’s
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or clinical datasets. Proficiency in Python and R, with strong experience in Linux/HPC environments and workflow automation. Track record of publications in high-impact journals and contributions to competitive