Hire the Best Quantum Computing Specialists

BACKGROUND: Quantum computing researcher with hands-on experience developing and deploying data science models on real quantum hardware. Achieved 96.1% correctness on IBM quantum systems with expertise in quantum machine learning, classification algorithms, and optimisation techniques. A proven track record in Python-based data pipelines, statistical modelling, and cross-functional collaboration. Experienced in translating complex technical problems into practical solutions with measurable business impact.

I help research teams and technical founders build reliable, testable scientific and quantitative software — from research prototypes and backtesting frameworks to production-grade execution systems, simulation engines, and performance optimization. I also conduct independent technical review of quantitative models, frameworks, and research. If you're dealing with slow code, messy data, a model you can't trust, or a research prototype that needs to become production, I can turn it into a robust, reproducible system. Credibility: PhD Physics (NYU, 2018). Quantitative Research at JPMorgan Chase (derivative pricing, 1M+ LOC C++ library). Max Planck Institute postdoc (general relativistic hydrodynamics simulations on HPC clusters, 1000+ cores). 13 peer-reviewed publications, 1,300+ citations, h-index 12. WHAT I DELIVER ▸ Quant & Options Engineering Backtesting frameworks (event-driven or vectorized), walk-forward, leakage checks Options analytics: Greeks, IV surfaces, Black-Scholes / numerical methods Research → production pipelines (clean architecture, tests, logging, monitoring) Execution integrations (e.g., IBKR) and robust order/risk handling Market data ingestion, cleaning, corporate actions handling, quality control checks ML and statistical models for time-series signals (proper time-series CV, no leakage) ▸ Scientific Computing & Research Tooling Custom software and research tooling for research-driven teams across physics, chemistry, biology, engineering and beyond — where the underlying problem is mathematical or computational. - Custom numerical solvers (finite volume / finite difference, spectral methods, particle methods), with stability and convergence analysis - Optimization engines (Bayesian optimization, gradient-based, evolutionary) for experimental design, formulation, and parameter search - Simulation frameworks for physical, chemical, and biological systems — from prototype to production-grade - Scientific data pipelines: ingestion, transformation, quality control, reproducible workflows - Verification and validation: benchmarks, unit tests, regression tests, convergence studies - Analysis tools, dashboards, and reporting infrastructure for research workflows - Air-gapped and reproducible deployments where IP sensitivity or regulatory context requires it ▸ Quantitative & Mathematical Review (NDA-protected) Independent technical review of quantitative models, frameworks, and research Verification of internal consistency, identifiability, hidden assumptions, and mathematical correctness Assessment of whether the formal structure supports the conclusions drawn from it Review of implementation against specification: numerical stability, edge cases, and code-to-specification fidelity ▸ HPC & Performance Engineering Performance engineering for large-scale scientific and ML workloads Distributed computing (MPI/OpenMP/CUDA), GPU optimization, memory and I/O tuning, parallel architectures, inference and training infrastructure at scale. Profiling, refactors, and speedups for codebases that need to run reliably under production load. WHY CLIENTS WORK WITH ME - Trustworthy engineering: I turn research prototypes into tested, reproducible production code - De-risking: I find failure modes early (leakage, overfitting, edge cases, scaling bottlenecks) - Maintainability: clean architecture, docs, and handover-ready delivery your team can extend - Communication: clear milestones, concise updates, realistic timelines — no surprises - Math ↔ engineering bridge: strong intuition for both theory and implementation details IDEAL PROJECTS - Quant strategy development, backtesting and research infrastructure - Options analytics and derivatives tooling - Mathematical review of quantitative manuscripts, white papers, or research frameworks - Independent validation of production models or implementations against specification - Market data pipeline and reproducibility upgrades - Performance optimization of slow Python/C++ codebases - Distributed training, GPU optimization, and inference serving for AI/ML workloads - Custom scientific or industrialized simulation or numerical software - Custom internal R&D tools for research labs and technical teams If this sounds like a fit, message me with a detailed brief with your current stack and success criteria — I'll let you know how I can help.

I'm an Online Tutor and Research Scholar having expertise in Maths and Physics. I'm Theoratical Physicist having reserch intrest in Quantum Computing ,Partical Physics and Gravitational Waves. I'm teaching from last 7 years . It's my passion to become a good Teacher. If you are facing any problem in understanding maths and physics ,let me help you. I will help you to overcome your weakness and help you to bulid problem solving techniques . I will make maths and physics easy for you. I have expertise in following subjets ; College Physics Calculus , Pre-Calculus , Calcullus 1,2,3,Multivarible Calculus AP Physics Physics 1,2,3 Mechanics Linear Algebra Solid State Physics Material Science Quantum Mechanics.Quantum computing , Quantum Optics Semiconductor Physics, Electronics General Relativity, Eletrodynamics, Electromagnitic Theory Group Theory String Theory Statistical Mechanics I have Experinence in, O/A Level Maths & Physics ( Edexcel, CIE, AQA , OCR ,WJEC , CCEA. University level coure and Research Proposal Writing fot Maths & Physics I teach via, Zoom , Google meet , Teams. Lets overcome exam fobia togrther. Thanks

I'm a full-blooded mathematician with scientific background in math, physics and computer science and basically interested in everything. :-) I worked for several years at university, did my PhD in the field of statistical image and data analysis, gave lectures and tutorials and supervised several students and theses. I'm very familiar with Boolean and linear algebra, analysis, probability theory, statistics, linear and nonlinear (convex) optimization and of course image and data analysis. Now, I'm working in the field of IT security, especially cryptography and side-channel analysis with machine learning and AI methods. Besides math (or more general, science), I‘m personally very interested in sports, fitness and health topics. I like to help with math assignments or programming tasks (including reimplementing the results of papers, e.g. in Python, R or Matlab), proofreading publications or theses, writing résumés and typing/formatting texts with LaTeX, and creating graphics with Tikz. Furthermore, due to my background in image processing, I have comprehensive experience in photo and video editing. As a native German I‘m happy to support in any translation or proofreading tasks involving German. At school I studied Latin for 9 years and really like the language, so I gladly offer any kind of support here as well. I’m also fluent in English and Swedish. Furthermore, I love writing calligraphy and handlettering and would be happy to realize your individual project. As I like thinking about mathematical problems, I enjoy solving logical quizzes, puzzles, riddles etc. and will be happy to support you with any kind of related projects (e.g. reviewing them for correctness, difficulty, clearity,…). Finally, I can also assist with tasks regarding the German tax system (e.g. Elster online, tax returns, VAT).

Working as a developer freelancer for the last 15 years: Data Science, Neural Networks, Python, Matlab, Fortran etc. Hold a Ph.D. in theoretical physics with expertise in strongly correlated electrons, optical lattices, and phase transitions. Fluent in Ukrainian and Russian, with advanced English proficiency, enabling me to write scientific papers and engage in effective communication as well as do EN-UA and EN-RU translations.

I am a computational physicist (PhD and postdoc in computational photonics) with extensive experience of solving physical/mathematical problems in both academia and industry. The following provides a summary of the work I have done: 1) Computational simulations of physical systems. This involved electromagnetics, electro and magnetostatics, current flow in ionic cells (dc and ac), diffusion, structural mechanics and charged particle tracing. 2) Optical system design and analysis. I specialize in optics so this topic has been a recurring part of my work. Particular examples include Fourier optics, gaussian beam propagation and aberration analysis. 3) Machine learning, mathematical optimization and signal processing. Physical problems in products naturally overlap with concepts in mathematical modelling. I have used signal processing, machine learning and nonlinear optimization and filtering methods for both 1D and 2D data. 4) I began my journey as an electrical engineer. I am familiar with electrical systems and have hands on experience of programming microcontrollers and FPGAs. As for tools, I am an advanced user of Comsol Multiphysics and opensource FEM code FeniCS. For scientific programming, I have extensively used Matlab, Python and Julia.