Research Scientist

Nomagic

Do you believe the path to general-purpose physical AI runs through noisy, real-world factory deployments? Are you excited by the challenge of turning the classical robotic stacks into the foundational training data for physical AI? Do you want to bridge the gap between world-class ML research and industrial-scale robotic execution? If your answers are yes, we should talk. At Nomagic, we are executing a humble pivot for general-purpose physical AI. We believe that physical AI is fundamentally a knowledge transfer problem - we are leveraging the "internet data" of robotics - massive deployment logs from real systems operating in production environments -  to bootstrap our efforts. We are looking for Research Engineers who will help us to build, train, and deploy foundational models that bring our fleet from a classical control stack to generalized AI mastery.

Constructor

OUR MISSION Constructor’s mission is to enable all educational organisations to provide high-quality digital education to 10x people with 10x efficiency.  With strong expertise in machine intelligence and data science, Constructor’s all-in-one platform for education and research addresses today’s pressing educational challenges: access inequality, tech clutter, and low engagement of students. PLEASE SEND YOUR RESUME IN ENGLISH ONLY. BRIEF JOB DESCRIPTION: Researches and prototypes the capabilities that power Constructor’s education products — applying AI and quantum through an education lens to improve how people teach, learn, and do research, rather than pursuing AI or quantum science as an end in itself. Forms hypotheses, designs and runs experiments, interprets results, and turns validated findings into working code that feeds product and engineering pipelines. Works independently, sets its own research agenda within the broader product strategy, and produces high-quality work that moves the platform and its users forward. Works closely with research associates, ML engineers, and technical leadership to make sure the work has real-world impact across the AI software development project. Requires 7+ years of applied research experience — ideally in education technology or applied AI — with a track record of turning research into products that ship. MISSION: Set and pursue a research agenda that produces results worth shipping — then make sure they land in the products and engineering pipelines that depend on them. EDUCATION: * PhD in Computer Science, Physics, Mathematics, or a related field — or equivalent applied research experience. A track record of impact through research that shipped into products, patents, or publications. DUTIES AND RESPONSIBILITIES:  * Set a research agenda aimed at real product and platform problems, within the broader strategy. * Design and run rigorous experiments; interpret results and decide what to take forward. * Turn validated findings into proof-of-concept code, drive it to production, and benchmark its impact in real products. * Deliver results as working proof-of-concept code first; reports, publications, or patents follow only where they add value — never in place of running code. * Mentor research associates, guide experimental direction, and partner with ML engineers to ship the work. QUALIFICATIONS AND EXPERIENCE: * 7+ years of applied research or research-engineering experience — ideally in education technology or applied AI. * Proven track record of research that reached production or had measurable real-world impact (publications/patents a strong plus). * Deep expertise in experiment design, modelling, and result interpretation. * Strong hands-on coding (Python, PyTorch) — ships runnable proof-of-concept code, not just designs; reproducible work via version control (GitLab) and experiment tracking (MLflow). * Able to work autonomously and balance scientific rigour against shipping speed. NICE TO HAVE (NOT OBLIGATORY): * Track record of moving research into production ML systems at speed. * Experience with AI-for-education products, or a quantum computing / quantum machine learning background. * History of mentoring researchers or leading a small research team. WHAT WE OFFER * 💻 Choice of work equipment (e.g., laptop, monitor, etc.) * 🇬🇧 English classes (iTalki – $130 monthly) * ⏰ Flexible schedule (we usually work between 09:00/10:00 and 18:00/19:00 CET or EET) * 👶 Newborn bonus (€500 per child) * 🧠 Patent remuneration * 🌴 Paid leave * 🧑‍💻 Remote work in locations without our offices * Hybrid work in locations with offices (2 days in-office, 3 days remote) Constructor fosters equal opportunity for people of all backgrounds and identities. We are led by a gender-balanced board committed to building a diverse and inclusive organisation where everyone can become their best self. We do not discriminate based on age, disability, gender identity, sexual orientation, ethnicity, race, religion or belief, parental and family status, or other protected characteristics. We welcome applications from women, men and non-binary candidates of all ethnicities and socio-economic backgrounds. We encourage people belonging to underrepresented groups to apply.

PhysicsX

ABOUT US PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. NOTE: WE ARE CURRENTLY RECRUITING FOR MULTIPLE LEVELS AND POSITIONS, HOWEVER PLEASE ONLY APPLY FOR THE ROLE THAT BEST ALIGNS WITH YOUR SKILLSET AND CAREER GOALS. WHAT YOU WILL DO  * Work closely with our machine learning engineers, simulation engineers, and customers to translate physics and engineering challenges into mathematical problem formulations. * Build models to predict the behaviour of physical systems using state-of-the-art machine learning and deep learning techniques. * Own Research work-streams at different levels, depending on seniority. * Discuss the results and implications of your work with colleagues and customers, especially how these results can address real-world problems. * Collaborate with colleagues beyond the research team to translate your models into production-ready code. * Communicate your work to others internally and externally as called for in paper publication venues, industry workshops, customer conversations, etc. This will involve writing for academic and non-academic audiences. * Foster a nurturing environment for colleagues with less experience in DS / ML / Stats for them to grow and you to mentor.   WHAT YOU BRING TO THE TABLE * Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. * Ability to scope and effectively deliver projects. * Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. * Excellent collaboration and communication skills — with teams and customers alike. * PhD in computer science, machine learning, applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: 1. operator learning (neural operators), or other probabilistic methods for PDEs; 2. geometric deep learning or other 3D computer vision methods for point-cloud or mesh-structured data; 3. generative models for geometry and spatiotemporal data (VAEs, Diffusion Models, Bayesian non-parametric, scaling to large datasets, etc.). * >2 years of experience in a data-driven role in a professional industry setting (excluding post-doc positions), with exposure to: * building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; * developing models for bespoke problem settings that involve high-dimensional data (spatiotemporal, geometric, physical); * iterating on network architectures and model structure, tuning and optimising for inductive biases, improved generalisability, and improved performance; * combining theoretical reasoning with empirical intuition to guide investigation; * formulating and running experiment pipelines to benchmark models and produce comparable results; * writing skills for communication complex technical concepts to peers and non-peers, tailoring the message for the required audience. * Publication record in reputable venues that demonstrates mastery in your field, and in particular the domains of interest listed above. Desirable venues include (but not limited to): NeurIPS, ICML, ICLR, UAI, AISTATS, AAAI, Siggraph, CVPR or TPAMI/JMLR. WHAT WE OFFER Build what actually matters Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind. Learn alongside exceptional people Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home. Influence over hierarchy We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected. Sustainable pace, long-term ambition Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person. And it doesn’t stop there … 🚀 Equity options - share meaningfully in the company you’re helping to build. 🏦 10% employer pension contribution - because investing in future matters. 🍽️ Free office lunches - to keep you energised and focused. 👶 Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most. 🍼 YellowNest nursery scheme - to help working parents manage childcare costs. ☀️ 25 days of Annual Leave (+ Public Holidays) - because taking time to rest matters. 🏥 Private medical insurance - 100% employee cover, giving you complete peace of mind. 💪 Wellhub Subscription - gain access to thousands of gyms, classes and wellness apps, supporting both physical and mental wellbeing. 👀 Eye tests - because good work depends on good health. 📈 Personal development - dedicated support for learning, development, and leveling up over time. 💛 Employee Assistance Programme (EAP) - confidential wellbeing support, available whenever you need it. 🚲 Bike2Work scheme and 🚆 Season ticket loan - to make getting to work easier and greener. 🚗 Octopus EV salary sacrifice - for a simpler, more sustainable way to drive electric. 🔎 Watch this space, we’re continuing to build this as we grow…   We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.