{"id":1700809,"url":"https://alion.io/job/quandela-quantum-information-scientist-tensor-network-simulations","title":"Quantum Information Scientist - Tensor Network Simulations","company":{"id":704,"name":"Quandela","domain":"quandela.com","url":"https://alion.io/company/quandela","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workable","truth_index":{"grade":"A","score":99,"open_postings":12,"ghost_share":0,"stale_share":0,"repost_share":0.083,"time_to_fill_p50_days":48,"computed_at":"2026-10-19T05:45:15Z"}},"role":"Quantum","role_family":"Quantum","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Paris, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":50000,"max_usd":148000,"period":"year","method":null,"sample_n":69},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"Julia","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-10-02T13:16:00Z","employer_posted_date":"2026-10-02","last_verified_at":"2026-10-19T23:17:20Z","board_verified":true,"closed_at":null,"days_open":17,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":17},"description":"About Quandela:\nQuandela is a global leader in quantum computing, designing, building, and delivering cutting-edge quantum solutions for research and industry. Its offerings include the most energy-efficient quantum computers for data centers, full-stack quantum computing solutions accessible via the cloud, and algorithm access services for academic and industrial customers.\nFollowing a pragmatic, step-by-step roadmap, Quandela has been deploying industrial-grade systems since 2023 while developing future generations of fault-tolerant quantum computers capable of scaling through the integration of thousands of photonic components. Quandela is committed to making quantum computing accessible to all in order to address the most complex industrial and societal challenges.\nLearn more at: Quandela | Leading Photonic Quantum Computing Solutions\nOur ambition is to build large-scale fault-tolerant quantum computers. Within Architecture, we develop methods to model and simulate our systems, understand their performance and guide future architecture choices.\nAbout this position:\nYou will work across our Device Physics and Quantum Information teams, bringing practical expertise in Tensor Network methods to develop a new simulation capability at Quandela.\nYou will apply and adapt approaches such as MPS, PEPS and related methods to quantum systems, circuits and future architectures.\nThe scientific questions will be defined together with the teams. Your role will be to determine how to address them: identify relevant literature, select numerical methods, develop simulations and assess their limitations.\n-\nWhat you'll do:\nAs a Quantum Information Scientist working on Tensor Network Simulations, you will:\nApply Tensor Network methods to the classical simulation of quantum systems, circuits and architectures. \nInvestigate scientific questions, review relevant approaches and select suitable numerical methodologies. \nDevelop research-grade simulations adapted to Quandela’s hardware and future SPOQC architectures. \nStudy entanglement growth, simulation of complexity and the propagation of physical noise. \nExplore different hardware configurations and architecture choices through numerical modelling. \nSimulate quantum algorithms and contribute to comparisons with relevant classical approaches. \nDevelop reusable scientific code and document methods so they can support research across different teams. \nContribute to scientific discussions, publications and future research directions around classical simulation.\n-\nHow you'll grow\nDuring your first 3 months: become familiar with Quandela’s architectures and research questions, investigate relevant methods and propose a first simulation approach.\nWithin 6-12 months: develop and validate your methods on concrete problems, build reusable tools and take increasing ownership of projects across Device Physics and Quantum Information.\nLonger term: become a key contributor to classical simulation at Quandela and extend your work toward future architectures, compilation or algorithm-level studies.\nRequirements\nWhat we're looking for:\nWe are looking for a researcher with practical Tensor Network experience and the autonomy to develop numerical approaches for open research problems.\nRelevant backgrounds include computational or quantum many-body physics, quantum information, mathematics and computer science. Previous experience in photonic quantum computing is not required.\nMust-have:\nPhD in Physics, Mathematics, Computer Science, Quantum Information or a closely related field, or equivalent research experience. \nPractical experience with Tensor Network methods, such as MPS, PEPS or closely related approaches. \nExperience developing or adapting numerical simulations for quantum systems, circuits or algorithms. \nAbility to move from an open scientific question to literature review, methodology selection, implementation and validation. \nScientific programming skills in Python, Julia and/or C++. \nAbility to assess the limits of a numerical method, including trade-offs between accuracy, computational cost and scalability. \nScientific autonomy and ability to collaborate across different research disciplines. \nProfessional English. \nImportant, but you can grow here:\nClassical simulation of quantum circuits or quantum algorithms. \nQuantum noise modelling. \nEfficient classical algorithms and benchmarking against classical baselines. \nQuantum compilation and native-gate-aware simulation.\nDevelopment of reusable scientific software and collaborative code practices. \nExperience working with hardware-specific constraints. \nBonus:\nExperience with tools such as ITensor, TeNPy or Quimb. \nDMRG, TEBD or other Tensor Network techniques beyond MPS / PEPS. \nQuantum-inspired or dequantised algorithms. \nPhotonic or spin-photonic quantum computing. \nExperience applying Tensor Networks to architecture evaluation or quantum-advantage studies. \nYou do not need experience across every application above. Practical Tensor Network expertise, strong numerical reasoning and the ability to develop a method when the path is not predefined are what matter most.\nPostdoctoral or equivalent research experience is particularly relevant, while strong recent PhDs with substantial hands-on Tensor Network experience are also encouraged to apply.\nBenefits\nJoin a research environment where advanced numerical methods can directly influence how future quantum architectures are evaluated and developed.\nWork across Device Physics, Quantum Information, FTQC and potentially Quantum Algorithms. \nApply Tensor Network methods to concrete hardware and architecture questions. \nTake scientific ownership of open research problems and progressively build a reusable simulation capability. \nContribute to publications, conferences and broader research directions as the scope develops. \nPlus:\nCompetitive compensation aligned with your experience and level of responsibility. \nCompany savings plan. \n100% health coverage through Alan. \nTransport reimbursement or sustainable mobility bonus. \nSwile meal vouchers. \nAccess to Gymlib. \nProcess:\nTalent Acquisition interview, 30-45 min \nScientific interview with members of the relevant research teams \nDiscussion of your previous research and Tensor Network experience \nTechnical scientific discussion \nReferences check \nFinal discussion with the team \nOffer \nThe scientific discussions are intended to understand how you approach an open research problem, identify relevant methods, assess their limitations and turn them into a practical numerical approach.\nBeyond that\n If you enjoy turning open scientific questions into numerical methods, this role offers the opportunity to develop Tensor Network simulation capabilities at Quandela and apply them directly to future quantum 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