We are looking for a Machine Learning Researcher with a combination of technical expertise, excellent skills in the field of applying machine learning algorithms, with a good appreciation of probabilistic modelling, statistical inference ideally applied to complex graph data. Ideally we seek an individual with a sound grasp of the science behind representing complex data, in particular graph theory, making intelligent connections and identifying causal relationships.
The Machine Learning Researcher will ideally have a rigorous foundation, such as a PhD in one of these areas, and maybe applied their ideas in a commercial or Post Doc project, applying those algorithms to the real world. We are looking for sound knowledge of machine learning, Bayesian methods, deep learning, probabilistic modeling and statistical inference. This individual will adopt an innovative approach able to bring their ideas and provide interesting solutions in our understanding of complex graph data. You will have the right mixture of inquisitiveness and rigour to follow through with the agreed tasks.
If you’re interested in Deep Learning, Deep Recurrent Networks for Semantic Compositionality, Neural Tensor Networks, text parsing, deep belief networks, recurrent neural networks and applying the latest algorithms and thinking to complex data then we’ll be interested to talk to you.
You will have the opportunity to contribute to this high performing team who seek to apply their knowledge in the high impact field of improving human’s capability in drug discovery.
This position will report to the Head of AI.
We offer a great opportunity to do what you like while doing something that will improve and save millions of people lives. If this challenge and opportunity excites you, please email your CV and a covering letter to firstname.lastname@example.org