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Position Overview: Solid Power is seeking a  Multiphysics   Modeling  Scientist  to join  our  t alented team working to revolutionize the battery industry through the development of  next - generation , all solid - state rechargeable batteries. Solid Power is a dynamic, fast - paced,  collaborative,  and innovative team environment. The preferred candidate will hav e  significant experience   working with  and using  m ultiphysics  simulations to model  chemical systems, heat transfer  dynamics , and  electrochemical  device behavior s .   The candidate will  be expected to  guide  synthetic approaches for dry, inorganic powders by modeling conditions in high-throughput powder reactors.   They will also work to update  existing   t hermal abuse models  that  integrate atomic-scale  reaction  kinetic s  with continuum - scale heat transfer   dynamics .  The   candidate  should be comfortable building  P2D / P4D  DFN  models and   using the se   approaches  to  guide experimental  planning ,  especially as it relates to battery formulation  improvements .     Job Duties: Develop continuum-scale reactor models for dry inorganic powder synthesis, coupling heat transfer, gas flow, mass transport, and reaction kinetics to guide reactor conditions and experimental planning.   Upgrade existing COMSOL-based implementations for thermal abuse modeling of ASSB cells.   Develop and validate mathematical models (both fundamental physics-based and data driven) to predict thermal, mechanical, and electrochemical behavior of ASSB materials, sub-assemblies, and finished cells.   Work with subject matter experts to develop experimental plans to isolate and quantify key model parameters, while producing minimal solvers that can be used by scientists/engineers.   Collaborate with subject matter experts to refine and continually validate modeling approaches, while employing best-practice workflows (i.e., mesh sensitivity analysis, ablation testing, unit testing, parameter sensitivity quantification).    Clearly explain to internal stakeholders the uncertainty in modeling predictions and write documentation on proposed upgrades that could be used to improve certainty.    Collaborate with data scientists on strategies to accelerate multiphysics modeling solvers and on strategies to guide virtual experiment prioritization (e.g. Bayesian approaches).   Collaborate with atomic-scale and coarse-grained modeling team members to translate their outputs into continuum-scale model inputs, assumptions, parameters, and validation targets.   Qualifications/Requirements: Master’s or Ph.D. in Computational Chemistry ,  Materials Engineering ,  Chemical  Engineering  or  a related  Electrochemical discipline.     2+ years of professional experience using commercial software to develop  m u l tiphysics  models of lithium-ion batteries.     A deep understanding of electrochemistry, preferably with at least some experience in battery systems.   Proficiency with  Python  and common data science libraries such as Pandas, NumPy,  and  SciPy .   Strong analytical and statistical problem-solving skills, having specific experience with configuring solvers for regression and parametrization tasks. &