About Us Deep Genomics is at the forefront of using artificial intelligence to transform drug discovery. Our proprietary AI platform decodes the complexity of genome biology to identify novel drug targets, mechanisms, and genetic medicines inaccessible through traditional methods. With expertise spanning machine learning, bioinformatics, data science, engineering, and drug development, our multidisciplinary team in Toronto and Cambridge, MA is … and protein-level mechanisms, analyze large biological datasets, and support the design of therapeutic molecules. This is an opportunity to work at the interface of machine learning and computational biology, making impactful contributions to drug discovery and therapeutic development. Key Responsibilities Develop and implement advanced machine learning models for RNA biology, systems biology, and structural biology to solve frontier challenges … in drug discovery. Collaborate with cross-functional teams (e.g., ML engineering, target discovery, and experimental biology) to drive research projects that identify novel drug targets and preclinical candidates. Design and execute computational and experimental studies to validate and improve model predictions. Stay informed about the latest advancements in machine learning and computational biology, and apply them to real-world challenges. More ❯
Cambridge, Cambridgeshire, United Kingdom Hybrid / WFH Options
Oxford Pharmagenesis Ltd
other UK offices (London, Cardiff or Cambridge). We are looking for a Data Scientist who has: a degree in a relevant discipline or equivalent experience (e.g. bioinformatics, computational biology, computer science). A PhD is preferred, preferably in life sciences prior experience in a biomedical/pharmaceutical or medical communications environment expert-level proficiency in Python and/or More ❯
team members. What we're looking for: PhD with at least 2 years of industry experience or MSc with 5 or more years of relevant experience in bioinformatics, computational biology, data science or a related field. Hands-on experience in developing and implementing multiple Nextflow pipelines in a production system. Excellent knowledge of Docker, git, the UNIX command line, R More ❯
partners in the collaboration are met.- Preparing presentations and written work for meetings with collaborators and for publication as journal articles. Experience required for the role - Experience in Computational Biology, Biostatistics, Statistics, Bioinformatics or a related field, with an associated Masters, or ideally PhD, qualification.- Experience of processing and analysing large biological datasets.- Expertise in programming using at least one More ❯
accountable for sustaining a diverse and inclusive environment. What You Will Contribute To Altos The Altos Labs Institute of Computation (IoC) is seeking an independent and highly motivated Computational Biology Scientist to build, maintain, and support our hybrid AI initiative to model cellular processes. The position will work in a multi-disciplinary research environment to assist investigators in algorithm development … mathematical models toward understanding mechanistic aspects of cellular processes with all experimental labs at Altos Labs. The ideal candidate is particularly interested in multi-scale (systems) biochemistry and molecular biology of reprogramming, a dynamic field that seeks to understand complex biological systems by integrating data about biochemical components and help design interventions that direct cellular states along desired trajectories. This … with a background in dynamical systems and mathematical modeling of biological systems. Be able to demonstrate significant AI experience/application in conjunction with a working understanding of cell biology and/or biophysics. The level of the position will depend on the qualifications of the selected candidate. Minimum Qualifications - PhD in Biology, Computational Biology, Computer Science, or closely related More ❯
Cambridge, Cambridgeshire, United Kingdom Hybrid / WFH Options
Nuclera
like Cypress and Playwright. You will play a vital role in ensuring the quality, performance, and reliability of both our cloud-based and on-instrument software. While no prior biology background is required, curiosity and a willingness to learn are essential. This role will be primarily working onsite in our Cambridge, UK office with occasional work remotely from home. About More ❯
and code, we are exploring chemical space previously unreached by natural biology. Constructive Bio is a spinout from Professor Jason Chin's laboratory at the MRC Laboratory of Molecular Biology in Cambridge. Learn more about the Chin lab achievements here: We recently secured $58 million Series A fundraising. Read more here: What we're looking for: We are looking for … model with in-house data to develop state-of-the-art sequence models for genetic sequence design. This is a unique opportunity to work at the frontier of generative biology and accelerate wet-lab experimentation. As our second ML hire, you'll help shape our ML infrastructure and define engineering standards for everything that follows. Responsibilities: Implement and benchmark state … the ML research and development lifecycle. Hands-on experience with PyTorch, Hugging Face libraries. Solid understanding of algorithms, data structures, and software design principles. Growth mindset and curiosity for biology - we'll teach you the rest Collaborative team player with excellent communication skills Desirable skills: Domain experience in computational biology, particularly genomic language models. Publications or open-source contributions in More ❯
collaborative environments and is committed to enabling colleagues to reach their full potential; Growth mindset - the desire to constantly expand your skillset and knowledge. Keen to learn more about biology, computational science, and medicine; Excitement about the Altos mission of restoring cell health and resilience to reverse disease, injury, and age-related disabilities. Minimum Qualifications - Masters or Ph.D. degree in … a quantitative/computational field such as computer science, artificial intelligence, mathematics, statistics, physics, or computational biology, or equivalent experience; Experience in developing machine learning models; Very strong programming skills, including experience with Python and deep learning libraries such as PyTorch or JAX; Experience in large-scale distributed optimization of machine learning models across multiple GPUs and nodes. Preferred Qualifications More ❯
identify opportunities for data and insight mining to accelerate research. Embed analyses and visualizations in automated reports. Who You Are Minimum Qualifications - PhD in interdisciplinary quantitative science such as Biology, Chemistry, Computer Science, Physics, etc. Relevant work experience in either an academic or industry setting. Working knowledge of cell biology and experience in large scale data analysis and statistical modeling More ❯
the support of a leading academic advisor, who'll provide you with the guidance and knowledge you need to develop your career. You will be part of the Quantitative Biology group and develop comprehensive Bayesian machine learning models for predicting drug toxicity in liver, heart, and other organs. This includes predicting the mechanism as well as the probability of toxicity … used to account for uncertainty in the inputs and propagate this uncertainty into the predictions. In addition, you will promote the use of Bayesian methods across safety pharmacology and biology more generally. You are also expected to present your findings at key conferences and in leading publications This project is in collaboration with Prof. Andrew Gelman at Columbia University, and More ❯