Role OverviewWe are sharing a specialised remote consulting opportunity for experienced Clinical, Microbiome, and Translational Research Scientists with doctoral-level qualifications and advanced expertise in microbiome research, metagenomics, clinical bioinformatics, biomedical data analysis, and precision medicine to contribute their scientific knowledge to advanced AI training and evaluation initiatives.
What You Will Do
Selected professionals will develop expert-level scientific problems, evaluate complex biological analyses, and assess AI-generated research outputs across microbiome science, clinical genomics, and translational medicine.
Why It Might Be a Fit
The work combines advanced biomedical research expertise with computational biology, statistical analysis, scientific literature evaluation, and structured benchmarking to improve the accuracy, reasoning, and reliability of advanced AI systems.
Requirements
- PhD in Microbiology, Bioinformatics, Computational Biology, Biomedical Sciences, Immunology, Epidemiology, or a closely related scientific discipline
- Hands-on research experience in an academic or industry laboratory
- Professional written and spoken English proficiency at C1 level or higher
- Deep expertise in microbiome science, metagenomics, clinical bioinformatics, or translational biomedical research
- Strong understanding of microbial communities, host–microbiome interactions, and relevant biological research methodologies
- Practical experience analysing 16S rRNA sequencing, shotgun metagenomics, virome, or other microbial sequencing datasets
- Familiarity with microbiome analysis tools such as QIIME2, Kraken2, MetaPhlAn, HUMAnN, or comparable applications
- Experience with metagenome assembly, genome binning, functional profiling, or microbial taxonomic classification is advantageous
- Strong knowledge of clinical genomics, biomarker discovery, precision medicine, or relevant translational research applications
- Familiarity with research resources such as TCGA, UK Biobank, or comparable clinical and biomedical datasets
- Experience in oncology genomics, immunology research, survival analysis, or integrating electronic health records with omics data is beneficial
- Practical proficiency in Python and/or R for scientific programming and quantitative biological analysis
- Strong statistical and machine learning capabilities relevant to high-dimensional biological datasets
- Familiarity with Bash, Linux environments, scientific workflow tools, or computational research pipelines is advantageous
- Demonstrated ability to critically evaluate scientific literature, experimental methodologies, and computational analyses
- Strong analytical reasoning, quantitative problem-solving, and biomedical research evaluation capabilities
- Postdoctoral or industry research experience in microbiome, clinical, or translational research is preferred
- Peer-reviewed publications, particularly first-author papers in relevant scientific journals, are highly valued
- Hands-on wet lab experience involving microbiology, molecular biology, or relevant biomedical techniques is advantageous
- Experience developing, reviewing, or benchmarking scientific content and research evaluations is beneficial
- Excellent written communication skills, including the ability to explain complex scientific concepts and document technical reasoning clearly
- Strong attention to detail and commitment to accurate, reproducible, and well-supported scientific conclusions
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