Improbable believes in a future where new, virtual worlds will augment human experience and become as meaningful, lasting and rich as the physical world. We call this the Multiversal Self.
Our platform, SpatialOS, lets developers transcend the limits of regular computation, allowing swarms of servers running in the cloud to cooperate in order to simulate worlds far larger and more complex than any single server could.
At Improbable, you are surrounded by people who want to improve everything and everyone around them, and who compel you to improve yourself. We’re motivated by the fulfilment of solving hard problems to achieve something profound and transformative.
...is to build scientific models that support our entire product offering and facilitate next generation decision support. We are a friendly, relaxed & inclusive team with an ambition to take agent-based modelling to the next level.
We model social systems as goal-oriented actors operating on imperfect information, “digitally twin” physical environments and infrastructure, and obsess with modularity to recast complex systems as combinations of simpler systems. Our applied scientists seek to balance cutting-edge research with pragmatism and creativity when designing new models.
Areas for Impact
- You will work broadly; conceptualising a system and writing a design document, converting that into a prototype model (we are language agnostic, and have worked in Python, Kotlin, Julia and R) and help educate others on your approach.
- Your role will combine literature reviews, conceptual modelling & prototyping to create scientifically defensible models that underpin our product offering
- Building pipelines to extract and integrate data from various sources, making it available to simulation engines and user interfaces.
- Your work will help military tacticians understand situations and plan more effectively, ultimately helping add to the stability and security of the world.
We’d like to hear if you if you identify with SOME of the following:
- Background and experience in scientific modelling (e.g. agent-based modelling, discrete-event simulation, system dynamics, bayesian networks, probabilistic programming, machine learning).
- Pragmatic coding ability - with fluency in at least one relevant programming language and the openness to learn and adapt to a variety of languages. We currently use Python, R, Kotlin, Julia and many related tools and libraries.
- An appreciation of software engineering workflow and openness to work closely with software engineers.
- Enthusiastic about continuously improving and rapidly developing new competencies.
- Effectively communicating with clients in person, in writing and with visualisation.
- An interest in academic research and an ability to review literature.
The best ideas are often the least expected and require new ways of thinking; that’s why our teams at Improbable are made up of an incredible range of talented people. Improbable is proud to be an equal opportunity employer. We do not discriminate based on race, ethnicity, colour, ancestry, national origin, religion, sex, sexual orientation, gender identity, age, disability, veteran status, genetic information, marital status or any other legally protected status.