Deep learning has only just started its transformative impact on the natural sciences. In Microsoft Research AI for Science we are seeking to solve some of the fundamental challenges in the molecular sciences with deep learning. For our lab in Cambridge, UK, or Amsterdam, NL we are seeking Machine Learning Researcher candidates at the intersection of chemistry and drug discovery. If you are passionate about this research area and believe you can make a lasting impact, we would love to receive your application. Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world. This post will be open until the position is filled. When submitting your application, include your CV with a list of publications as an attachment. Qualifications Required: Track record in Deep Learning research, as evidenced by a PhD or similar research experience in the field. Experience designing and optimizing new architectures and algorithms, and running experiments and analyses to study their performance. Experience in Python software development, ideally demonstrated by published software projects (e.g., github). Experience in developing and implementation of deep learning systems (e.g., in PyTorch or JAX). Preferred: Experience working with graph data, reinforcement learning, and/or generative models. Experience with molecular data in real-world drug discovery. Track record of publications in ML conferences and/or scientific journals. Responsibilities Contribute to and drive an ambitious, high-impact, machine learning research agenda in the molecular sciences. Design and develop new machine learning models and algorithms. Write code to run and evaluate large scale ML experiments. Work with internal and external partners to deploy and evaluate models and workflows. Prepare technical papers and presentations. Working on a day-to-day basis with an international and interdisciplinary research team on one overarching research goal.