7 of 7 Remote/Hybrid Permanent Biology Jobs

closely with clinicians to understand and support their reporting and analytical needs Qualifications Mandatory qualifications and experience: A postgraduate degree in computer science, statistics, biology or a related quantitative discipline. Expert R (R Studio) programming skills for manipulation/cleaning, report generation, visualisation of data, statistical analysis and modelling Experience ...

Data Scientist - Contractor (Quantitative Biosciences) Location: Rahway, NJ (Hybrid: 3 days onsite, 2 days remote) Overview Join a cutting-edge and innovative Quantitative Biosciences department focused on advancing drug discovery through computational science, high-throughput ...

Developing data analytic pipelines and novel methodologies for scientific applications Cambridge; £45,000 to £75,000 DoE + Benefits This hybrid-style role combines a healthy dose of data science analytics, scientific project understanding and ...

scientific stakeholders in areas such as genomics, NGS, translational research, or multi-omics Strong communication and relationship-building skills Desirable Experience Bioinformatics or computational biology background transitioning into commercial roles Experience in AI/ML, spatial biology, digital pathology, or precision medicine environments Exposure to cloud platforms, data governance ...

+ Equity 🧬 AI Biotech Startup | Full-time About Us I'm working with an AI-first biotech company building foundation models for biology and chemistry to radically accelerate drug discovery. By combining probabilistic modelling, large-scale biological datasets, and generative machine learning, they're creating systems capable of reasoning across … similar frameworks Experience training large models on distributed infrastructure Strong software engineering and systems design capabilities Nice to Have Background in computational biology, drug discovery, or bioinformatics Experience working with molecular, genomic, or protein datasets Familiarity with diffusion models, energy-based models, or probabilistic generative methods Publications ...

support to help you make Barcelona home if it's not already. Hard Technical Challenges The company sits at the edge of machine learning, biology, and experimental science. Some of the hardest problems you'll work on include: Learning from sparse biology. Biological data is noisy, expensive, high-dimensional … decisions. We care more about depth, judgment, and evidence of exceptional work than credentials. You may have PhD-level training in machine learning, physics, biology, chemistry, applied mathematics, computational biology, or another systems-oriented discipline. You should have strong foundations in one or more of: applied mathematics, statistics, optimisation, probabilistic ...

Track record of translating cutting-edge research into scalable production systems Highly Desirable Experience applying machine learning to protein engineering, antibody discovery, or computational biology Familiarity with antibody sequence datasets, immune repertoire modelling, or protein language models Experience with structural biology data including AlphaFold, protein embeddings, or molecular simulation outputs … prediction, or therapeutic optimisation workflows Experience with diffusion models, graph neural networks, or generative protein design approaches Publications in machine learning, protein modelling, computational biology, or AI for Science Why Join? Build frontier AI systems focused on one of the most impactful areas in modern biotechnology Help create foundation models ...