Computational Fusion Scientist / Engineer

Meraki Labs is a deep tech venture studio based in Bangalore, founded in 2020 by serial entrepreneur Mukesh Bansal (co-founder of Myntra and Cult.fit). The studio works on applied AI products and other deep tech incubations, operating as a sector-agnostic incubator focused on building and backing early-stage, tech-driven companies.

Focus Area: Plasma Physics & Multi physics Simulation

We are looking for an exceptional Computational Fusion Scientist / Engineer to develop high-fidelity numerical models and simulations of fusion plasmas and reactor systems at Meraki Labs.

You will work at the intersection of plasma physics, numerical methods, high-performance computing, and fusion engineering, developing simulation capabilities that help us understand plasma behaviour, optimize reactor configurations, predict performance, and guide experimental and engineering design.

This is a highly technical role for someone who enjoys translating first-principles physics into computational models.

• Develop numerical models of fusion plasmas using MHD, kinetic, fluid, hybrid and/or particle-based approaches.

• Simulate plasma equilibrium, stability, confinement, transport, heating and particle behaviour.

• Model relevant plasma phenomena including:

  • Magnetohydrodynamic instabilities

  • Plasma transport and turbulence

  • Magnetic field configurations and plasma equilibrium

  • Particle orbits and energetic particle behaviour

  • Plasma heating and current drive

  • Plasma-wall interactions

  • Fusion reaction rates and power balance

• Develop multiphysics simulations coupling plasma behaviour with electromagnetics, thermal systems, structural mechanics and other reactor physics where required.

• Build reduced-order and system-level models to rapidly explore large fusion reactor design spaces.

• Perform parameter sweeps, sensitivity analysis and optimization of plasma and reactor configurations.

• Develop, validate and benchmark simulation codes against analytical models, published results and experimental data.

• Use and extend established fusion/plasma simulation tools where appropriate, while developing proprietary computational capabilities where needed.

• Build scalable simulation workflows for HPC clusters, GPUs and parallel computing environments.

• Translate simulation results into actionable engineering requirements and reactor design decisions.

• Work closely with plasma physicists, magnet engineers, mechanical engineers, controls engineers and experimental teams.

M.Tech / MS / PhD in Plasma Physics, Nuclear Engineering, Computational Physics, Applied Mathematics, Aerospace/Mechanical/Electrical Engineering, or a closely related field.

Strong foundation in several of the following:

• Plasma physics

• Magnetohydrodynamics (MHD)

• Electro magnetics

• Fluid dynamics

• Kinetic theory

• Numerical methods

• Partial differential equations

• Computational physics

Strong programming capability in Python and C/C++ and/or Fortran.

Experience with numerical techniques such as:

• Finite Difference

• Finite Volume

• Finite Element

• Spectral methods

• Particle-in-Cell (PIC)

• Monte Carlo methods

• ODE/PDE solvers

Experience with parallel computing using technologies such as MPI, OpenMP, CUDA or GPU computing is highly desirable.

Experience with one or more fusion/plasma simulation frameworks such as MOOSE, BOUT++, GENE, GS2, Gkeyll, JOREK, NIMROD, M3D-C1, TRANSP, ASCOT, OpenMC or equivalent tools.

Experience in any of the following would be particularly valuable:

• Tokamak or stellarator physics

• Magnetic confinement fusion

• Field-reversed configurations or other alternative confinement concepts

• Inertial or magneto-inertial fusion

• Plasma equilibrium and stability

• Neutronics and fusion blanket modelling

• Fusion reactor systems modelling

• Scientific machine learning / physics-informed ML

• Large-scale HPC simulation

Beyond specific software experience, we are looking for someone who can start with a physical problem, formulate the governing equations, determine the appropriate numerical approach, implement the model, validate it, and use the results to make real fusion reactor design decisions.

The ideal candidate combines the rigor of a computational physicist with the practical mindset of an engineer building a fusion machine.