Neural Information Processing Systems Conference (NeurIPS 2019)
We will be attending and presenting our latest research on machine learning applied to drug discovery and development at NeurIPS 2019. You can find us at the exhibitor area on booth number 10. If you’d like to get in touch before or during NeurIPS, contact us.
Machine learning represents a huge opportunity in healthcare, particularly in drug discovery and development. Our team of machine learning researchers, engineers and biomedical scientists form a unique collaborative environment which leverages expertise in artificial intelligence and science to drive innovation, bring a data-driven approach to the drug discovery and development process, with the ultimate goal of providing better and more personalised medicines to patients faster.
NeurIPS is one of the flagship events in machine learning and a place where some of the greatest minds in the field converge to discuss the latest innovations, showcase their research, and explore how this research can be applied across every sector, including healthcare. We look forward to discussing potential projects with the NeurIPS crowd.
BenevolentAI research at Neurips 2019
We are proud to present one of our latest research on AI applied to drug development at the Women in Machine Learning workshop. Women in Machine Learning’s mission is to increase the number of women in machine learning, help women succeed professionally, and enhance their experience and impact in the machine learning community.
Rosalind: gene prioritization with tensor factorization
Author: Saee Paliwal
Join us at the NeurIPS learning meaningful representations in life (LMRL) workshop. LMRL will feature some of the best efforts in biology and machine learning to spur the next generation of data-driven biological problem-solving. An emphasis on interpretable learning of structure and principles will be applied to work on the level of the genome, molecules, cells, and phenotype.
Amyotrophic Lateral Sclerosis endotype detection using RNA-sequencing and Bayesian biclustering
Authors: Craig A. Glastonbury*, Povilas Norvaisas*, Árpád Vezér, Aaron Sim, Francesca Mulas, Hamish Tomlinson, Poojitha Ojamies, Joanna Holbrook, Paídí Creed.
Towards a Disease-Relevant Benchmark for Co-expression Module Detection
Authors: Árpád Vezér, Eirini Arvaniti, Craig A. Glastonbury, Francesca Mulas, Povilas Norvaisas, Poojitha Ojamies, Aaron Sim, Paídí Creed.
Demo | Booth 10
Join us at our booth where we’ll show you demos of our AI and machine learning tools that help our scientists to accelerate our journey from data to medicines.
We have been looking at a holistic approach to drug development from target identification, molecule design up to clinical development with the perspective to develop precision treatments tailored to specific patient groups and move away from the current “one-size-fits-all” treatments. Here is a short intro video to what we do:
If you aspire to truly make a difference, you will find us on booth 10. Chat with our team about job opportunities at BAI, or discuss possible collaborations and partnerships. Alternatively, if you’d like to get in touch prior the conference, you can contact us via the form below. We look forward to hearing from you.
If you don’t find any jobs suitable for you, please reach out anyway. We are looking for brilliant minds, always!