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Senior Scientist
2 weeks ago
Your role at Monumo will help us solve complex interdisciplinary problems. As part of our simulation team, you’ll join an ongoing effort to develop our internal capabilities for modelling and optimising novel motor designs. You will also collaborate closely with our other teams, including motor design and ML experts, to develop efficient models for a wide range of electric motors and physical phenomena. Together, the other teams will want to use your new features millions and millions of times. About Us At Monumo, we are united by a shared commitment to addressing environmental challenges and finding innovative solutions to complex problems. Together, we are shaping a future where technology meets sustainability. We are combining human ingenuity with deeptech intelligence to deliver more sustainable designs and solve engineering problems impossible by conventional means. Our methodology opens the door to optimal engineering solutions and disruptive new design ideas, that would be impossible, or at the very least improbable, without this blend of great engineers and compute power. Our focus, at present, is on the engineering design problem of electric motors; a mature, but increasingly vital technology with plenty of room for improvement. However, the techniques and the creativity employed to solve the engineering and technical problems of improving motor performance can be applied to other challenges. The tools we are creating can be applied to clean energy generation, aviation, heavy industry, manufacturing, robotics… there's a lot to optimise Every effort must be made to solve the climate crisis, to protect the Earth's resources, reduce the materials we use, increase the efficiency and performance of things we make and reduce their impact. Electric motors account for 50% of worldwide electricity consumption and are a key element in transport decarbonisation. We want Monumo to play a meaningful part in this change. We are a well-funded start-up based in central Cambridge and Coventry, UK. This role is within our Simulation team, based in Cambridge. Our core team brings together complementary skills and expertise from Arm, Microsoft Research, DeepMind, and academia. We really value everyone's individual experience and the different perspectives, skills, and humour they bring to our team. About the job The responsibilities of the role include: Researching new computational physics techniques and acceleration methods. Expanding our multiphysics simulation engine by developing in-house Partial Differential Equation (PDE) solvers or integrating open-source tools (e.g. ElmerFEM, FEniCSx). Taking the initiative to research, and collaborate internally, to solve problems in unfamiliar domains. Delivering regular updates internally, and where necessary externally to our customers & partners. Reading and sharing papers, attending conferences and developing new IP. What you’ll bring that we value You may come from a physics, computer science, maths or engineering background – we're very open minded about that. Below are some of the skills we’re looking for in this role. Don’t worry if you don’t tick all of them More important is your willingness to grow and learn new things. Important: Excellent research and problem-solving skills PhD or equivalent experience in industry Python for numerical computing (e.g. numpy) Physics experience, particularly electromagnetism, solid mechanics, and/or thermal models Experience using numerical methods (e.g. finite elements) for solving PDEsNice to have: Compiled languages (e.g. C / Rust / Zig / Fortran / Julia), and integrating high-performance code with Python (e.g. numba, extension modules) Our promise to you Salary – as we are open to different applications, we will discuss this directly with you during our application process. 30 days holiday a year, plus 8 bank holidays and additional time off between Christmas and New Year to reflect on the past year and prepare for the year ahead After every 5th year at Monumo, you can take a paid sabbatical for 30 days to travel, work on personal projects or simply to recharge and reboot Shared full pay for maternity, paternity or adoption leave (subject to length of service) #J-18808-Ljbffr
