Description

We are looking for people to help us develop research-grade AI systems and train LLMs with a solid grasp of the biological ground truth. Your primary task will be developing the pipeline that would inject biological knowledge into LLMs. More specifically, you will be responsible for teaching LLMs how to reason about aging and how to discover novel anti-aging gene targets and geroprotectors. This role requires both biological and programming background, especially in ML and AI fields. The position requires writing and submitting reviews and original research papers to Q1 journals. Other routine activities include dataset scouting and preprocessing, building PoC AI applications, systematic reviews of the current state of the LLM and aging fields, critical review of literature and methodologies.

Requirements

Master’s/PhD degree in bioinformatics, CS, or biology. 6+ years in Python (async/aiohttp, ML & stats libraries, transformers, data visualization), 2+ years in R, including omics-related Bioconductor packages, 5+ years in omics & bioinformatics research, from raw data to conclusions (DEG, GSEA, survival analysis; KEGG, GO, GEO, UniProt, etc.), strong knowledge of omics platforms (DNAm, transcriptomics, proteomics, single-cell), research excellence: hypothesis-driven work, experimental design, advanced statistics, independent academic writing, aging biology expertise: aging clocks, hallmarks of aging, geroprotectors, animal models, proven experience with AI/ML in biology (AI agents, fine-tuned models, or public datasets/models), strong AI literacy (LLMs via API, deep learning fundamentals, AI risks awareness), academic publishing track record (≥5 publications/preprints; ≥2 in aging/longevity), C1 English (academic writing, clear communication), ability to work independently, under pressure, and align research with business priorities.

Business Development Manager(s) — Conferences & AI Platform Technologies

Description

Requirements

Insilico Medicine