Applied Research Associate

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    "description": "<p><span style=\"font-size: 12pt\">As an Applied Research Scientist in probabilistic computing, you will work on the development and refinement of algorithms that leverage the unique entropy-driven capabilities of our PPU. You will move beyond binary logic, investigating how p-dits and Gaussian units are used to outperform traditional CPU/GPU architectures and quantum annealers.</span></p>\n<p><span style=\"font-size: 12pt\">This is a 'full-stack' research role which means that you will move from mathematical theory to simulator verification in Python, as well as creating pseudo-code specifications for our hardware engineering team. A core part of this role involves understanding the specific physical nature of Quantum Dice’s hardware to ensure that algorithmic development is perfectly aligned with our hardware roadmaps.</span></p>\n<p><br></p>\n<p><span style=\"font-size: 12pt; font-weight: bold\">You will work on:</span></p>\n<p><span style=\"font-size: 12pt\">1) Algorithm</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Research and develop novel extensions to Adaptive Parallel Tempering (APT), Simulated Quantum Annealing (SQA) and similar algorithms + implementing new algorithmic paradigms that move beyond traditional simulated annealing.</span></li>\n<li><span style=\"font-size: 12pt\">Investigate the use of p-dits and Gaussian units within optimisation frameworks to improve convergence and solution quality.</span></li>\n<li><span style=\"font-size: 12pt\">Develop Boltzmann machines and Bayesian learning frameworks specifically geared toward causal and explainable AI, ensuring transparency in complex model outputs.</span></li>\n<li><span style=\"font-size: 12pt\">Continuous improvement of automated parameter prediction system, creating self-optimising loops that allow the submission script to adapt to problem-specific landscapes without manual intervention.</span></li>\n</ul>\n<p><span style=\"font-size: 12pt\">2) Benchmarking and industrial integration</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Define rigorous performance metrics and plan comprehensive test suites for industrial-scale problems (e.g. logistics, finance, or materials science).</span></li>\n<li><span style=\"font-size: 12pt\">Work on the integration of probabilistic kernels into automated decision-making engines.</span></li>\n<li><span style=\"font-size: 12pt\">Conduct competitive benchmarking against state-of-the-art classical solvers and quantum backends.</span></li>\n</ul>\n<p><span style=\"font-size: 12pt\">3) Hardware-algorithm co-design</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Maintain and extend our Python-based simulators to verify algorithmic performance.</span></li>\n<li><span style=\"font-size: 12pt\">Translate research into pseudo-code for hardware implementation. You will learn the specifics of how algorithms are physically implemented on Quantum Dice’s architecture to ensure your designs are hardware-efficient.</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 12pt; font-weight: bold\">Who you are:</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">PhD (preferred) or a research-heavy MSc in Physics, Computer Science, Applied Mathematics or a related field.</span></li>\n<li><span style=\"font-size: 12pt\">Familiarity with probabilistic algorithms, ideally also having implemented MCMC methods, Gibbs sampling, and energy-based models.</span></li>\n<li><span style=\"font-size: 12pt\">Familiarity with Bayesian inference, Causal AI, and the mathematical foundations of Boltzmann machines.</span></li>\n<li><span style=\"font-size: 12pt\">Ability to review Python code and translate algorithms into hardware-agnostic pseudo-code.</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 12pt; font-weight: bold\">Nice to have:</span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">Experience with hardware-aware algorithm design (e.g., FPGAs, ASICs, or photonic circuits).</span></li>\n<li><span style=\"font-size: 12pt\">Knowledge of combinatorial optimization (Ising models, QUBO) and its application in industrial decision-making.</span></li>\n<li><span style=\"font-size: 12pt\">Previous experience in a deep-tech startup environment.</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 12pt\"><span style=\"font-weight: bold\">Why join us?</span></span></p>\n<ul>\n<li><span style=\"font-size: 12pt\">It's an exciting time to work in probabilistic computing and you’ll be defining the libraries for an entirely new class of computer.</span></li>\n<li><span style=\"font-size: 12pt\">We maintain strong ties to the University of Oxford, offering a vibrant intellectual environment and access to world-leading experts.</span></li>\n<li><span style=\"font-size: 12pt\">Our technology targets critical real-world sectors, including logistics, drug discovery, and climate modeling.</span></li>\n<li><span style=\"font-size: 12pt\">We are a diverse team of passionate thinkers meeting builders. We value curiosity, transparency and a good sense of humour.</span></li>\n</ul>\n<p><br></p>\n<p><span style=\"font-size: 12pt\"><span style=\"font-weight: bold\">Quantum Dice is an equal opportunity employer.</span> We celebrate diversity and are committed to creating an inclusive environment for all employees.</span></p>",
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