Quantitative Researcher - PhD

The RoleAmunra is seeking exceptional Quantitative Researchers with PhDs in mathematically rigorous scientific disciplines.This is not a conventional quantitative-finance research role.We are particularly interested in scientists trained to reason about high-dimensional interacting systems, stochastic processes, nonlinear dynamics, emergence, collective behaviour, critical phenomena, networks, information, scaling, and systems far from equilibrium.Researchers will investigate fundamental questions about the structure and dynamics of financial markets and translate scientific findings into rigorous quantitative methodologies and computational systems.The role sits at the intersection of fundamental research, applied mathematics, computational science, and quantitative finance.Researchers will have substantial freedom to formulate hypotheses, develop mathematical frameworks, design numerical experiments, work with large empirical datasets, and contribute to Amunra's proprietary research programme.Research AreasDepending on background and expertise, research may involve:Complex adaptive systemsStatistical mechanics and non-equilibrium systemsInteracting stochastic systemsNonlinear and stochastic dynamicsCritical phenomena and phase transitionsScaling laws and universalityMultifractal and multiscale systemsLong-memory and anomalous diffusionRandom matrix theoryInformation theory and statistical inferenceNetwork science and interacting networksCollective behaviour and emergenceDynamical stability and instabilityStochastic processes and stochastic differential equationsHigh-dimensional statistical systemsSpatiotemporal systemsEndogenous dynamics and interacting agentsComputational modelling and simulationMachine learning for scientific discoveryRepresentation learning for complex systemsInference in noisy and non-stationary systemsFinancial markets will serve as the principal empirical domain in which these ideas are developed, tested, and applied.What You Will DoYou will:Formulate original research questions concerning complex financial systemsDevelop mathematical, statistical, and computational models of interacting market phenomenaIdentify measurable structure in large, noisy, high-dimensional, and non-stationary datasetsInvestigate dynamics across multiple timescales and levels of aggregationStudy nonlinear dependence, collective behaviour, structural change, and emergent phenomenaDevelop novel quantitative measures and mathematical representationsFormulate hypotheses from first principles and subject them to rigorous empirical testingDistinguish genuine structure from statistical artefacts, spurious relationships, and overfittingDesign numerical experiments, simulations, and computational research pipelinesWork with large-scale financial datasets and high-performance research infrastructureCollaborate across physics, mathematics, machine learning, quantitative finance, and engineeringTranslate successful research into robust computational methodologiesContribute to Amunra's proprietary scientific research and intellectual propertyResearchers are expected to challenge established assumptions and develop new approaches where conventional methodologies are insufficient.Required QualificationsA PhD is mandatory.We are particularly interested in doctoral backgrounds including:Theoretical PhysicsStatistical PhysicsMathematical PhysicsQuantum Field TheoryCondensed Matter PhysicsComplex Systems / Complexity ScienceStatistical MechanicsNonlinear DynamicsDynamical SystemsApplied MathematicsProbability and Stochastic ProcessesNetwork ScienceInformation TheoryComputational PhysicsComputational ScienceFluid Dynamics / TurbulenceQuantum InformationMathematical or Computational Biology involving complex systemsOther closely related mathematically intensive disciplinesExceptional candidates from adjacent fields may be considered where their doctoral research demonstrates significant mathematical, statistical, or computational depth.Scientific ProfileStrong candidates will typically demonstrate several of the following:Deep mathematical maturityExperience studying systems with many interacting degrees of freedomStrong foundations in probability, statistics, and stochastic processesExperience with nonlinear, non-equilibrium, or high-dimensional systemsAbility to move between theoretical reasoning and empirical investigationExperience extracting structure from noisy datasetsFamiliarity with numerical methods and computational modellingAbility to formulate models from first principlesComfort working beyond assumptions of equilibrium, stationarity, independence, and linearityStrong scientific skepticism and experimental disciplineEvidence of original research rather than solely implementation of established techniquesPublication quality, originality, and intellectual depth matter more to us than publication count.Computational SkillsCandidates should be comfortable conducting computational research independently.Strong proficiency in Python or an equivalent scientific-computing language is expected.Experience with some of the following is advantageous:NumPy / SciPyPyTorch or JAXNumerical optimisationMonte Carlo methodsStatistical computationTime-series analysisGraph and network computationParallel and high-performance computingC / C++ / JuliaGPU computingLarge-scale datasets and distributed computing environmentsResearchers are not expected to be software engineers, but they must be capable of implementing and rigorously testing their own ideas.Financial ExperiencePrior experience in finance is not required.Amunra is deliberately interested in researchers capable of bringing mathematical tools, scientific methods, and intellectual traditions from outside conventional quantitative finance.Candidates with financial-market experience are welcome, but scientific depth takes precedence over familiarity with standard financial models.Researchers entering from physics, mathematics, or adjacent sciences will be expected to develop a rigorous understanding of financial markets as an empirical system.What We Are Not Looking ForThis role is unlikely to be suitable for candidates whose experience is primarily in:Conventional equity factor modellingStandard financial econometrics without broader scientific research depthDiscretionary investment researchFundamental equity researchRoutine implementation of established quantitative strategiesDashboard analytics or business intelligenceGeneric data sciencePure signal mining without a deeper scientific hypothesisAmunra is seeking researchers interested in understanding the structure and dynamics of markets, rather than simply fitting predictive models to financial time series.Research CultureAmunra is being built as a deliberately interdisciplinary research environment.A theoretical physicist may work alongside a statistical physicist, complexity scientist, applied mathematician, network scientist, machine-learning researcher, quantitative researcher, engineer, and experienced market practitioner.We are interested in ideas that cross disciplinary boundaries—but only when they survive rigorous mathematical and empirical scrutiny.Researchers are expected to communicate across disciplines, challenge assumptions, and maintain exceptionally high standards of scientific evidence.Intellectual independence is encouraged. Scientific rigor is mandatory.Candidate StandardWe expect this role to be highly selective.We look for:Scientific depth — A serious command of your doctoral field.Originality — Evidence that you have developed ideas, not merely applied existing methods.Mathematical rigor — Comfort reasoning formally about difficult systems.Empirical discipline — The ability to separate compelling narratives from statistically defensible results.Computational ability — The capacity to turn theoretical ideas into reproducible numerical experiments.Intellectual range — An interest in learning across physics, mathematics, computation, and financial markets.Research ambition — A desire to work on questions for which the methodology may not yet exist.