Senior Research Scientist
Your role is to lead research that contributes to our ground-breaking technology demonstrators, ensuring that Improbable’s decision support tools, training systems and digital twins embody robust and cutting-edge science.
The Research team brings together experienced researchers and software engineers from multiple disciplines interested in improving the performance, validity, richness and effectiveness of simulations of complex systems. We regularly publish, and work closely with both industry and academic collaborators; this year, two of our researchers received Royal Society awards for their collaboration with leading academics from the Turing Institute, and Leeds, Exeter and Warwick Universities.
Areas for Impact
- Become rapidly well-versed on the state-of-the-art in relevant technical areas, such as agent-based models, evolutionary computing and machine learning
- Pursue independent research towards our strategic objectives. This requires translation of ambitious but often vague objectives into concrete research proposals, with a realistic assessment of the necessary resources and expected outcomes
- Take a lead role in driving the strategy and execution of Research at the team level; define directions, set goals, mentor junior researchers, and drive change to support its impact, and growth
- Test and demonstrate ideas effectively in code. Be comfortable working in at least one high-level language (like Python), and to a high engineering standard when appropriate
- Maintain existing relationships and foster new links with academic and industrial research partners
We'd like to hear from you if you identify with the following:
- PhD in statistics, machine learning, computer science or a simulation-related field
- Extensive experience in scientific computing with experience developing novel tools and methodologies for scientific modellers that allow them to model complex socio-technical systems efficiently, realistically and robustly
- Track record of high profile research as evidenced by publications, patents and/or conference talks
- Scientific programming skills in, e.g., Python, Julia, R or C++
- Experience with deep learning and/or probabilistic programming libraries in Python (e.g. Pytorch, Pyro) is desirable
- Excited to be able to deliver functionality for agent-based models that exceeds the state-of-the-art, and have it used by the most discerning customers in the defence and security industry
- Experience with agent-based models or microsimulations in any domain
Nb: While we think the above experience could be important, we can’t predict the future and so we’re keen to hear from applicants that believe they have valuable experience. If you identify with the team & mission, but not all of the suggestions, then please still apply
Improbable is determined to foster an environment where people can do their best work and feel like they belong. We believe a healthy culture, strong values and contribution from a diverse range of individuals will help us to achieve success.
We do not discriminate based on race, ethnicity, gender, ancestry, national origin, religion, sex, sexual orientation, gender identity, age disability, veteran status, genetic information, marital status or any other legally protected status.
Life at Improbable
Diversity, inclusion & belonging
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Date posted: 2022-01-20