{"html":"<p><strong>Job Title:</strong> Clinical, Microbiome &amp; Translational Research Scientist (PhD)</p><p><strong>Job Type:</strong> Contractor</p><p><strong>Location:</strong> Remote(Worldwide)</p><p><strong>Job Summary:</strong> In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input.</p><h4>Key Responsibilities</h4><ul><li>Design and write challenging, expert-level scientific problems in microbiome/metagenomics, clinical and translational bioinformatics, and related life sciences, with clear, verifiable solutions.</li><li>Review and evaluate AI model outputs for scientific accuracy, rigor, and depth of reasoning, catching subtle errors non-specialists would miss.</li><li>Develop detailed rubrics and reference answers grounded in primary literature and established methodology.</li><li>Apply domain expertise across areas such as 16S and shotgun metagenomics, virome/host-microbiome analysis, biomarker discovery, clinical genomics, and omics-driven precision medicine.</li><li>Provide clear written explanations of your reasoning so other experts can follow and validate it.</li><li>Meet quality standards through iterative feedback and peer review.</li></ul><h4>Required Qualifications (MUST)</h4><ul><li>PhD in Microbiology, Bioinformatics, Computational Biology, Biomedical Sciences, Immunology, Epidemiology, or a closely related field.</li><li>Hands-on research experience in an academic or industry lab (wetlab experience is a plus).</li><li>Professional written and spoken English (C1 or higher).</li></ul><h4>Preferred Skills</h4><ul><li>Postdoctoral or industry research experience in microbiome, clinical, or translational research.</li><li>Publication record, ideally first-author papers in relevant journals.</li><li>Microbiome tools: QIIME2, Kraken2, MetaPhlAn, HUMAnN, MAG assembly/binning, virome analysis.</li><li>Clinical/translational: TCGA, UK Biobank, biomarker discovery, survival analysis, EHR + omics integration, oncology/immunology genomics.</li><li>Statistics and ML for high-dimensional biological data.</li><li>Programming: Python and/or R (required in practice), Bash, workflow tools.</li><li>Experience reviewing, benchmarking, or writing scientific content.</li></ul>"}