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Research Data Scientist

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PhysicsX is a deep-tech company of scientists and engineers, developing machine learning applications to massively accelerate physics simulations and enable a new frontier of optimization opportunities in design and engineering.

Born out of numerical physics and proven in Formula One, we help our customers radically improve their concepts and designs, transform their engineering processes and drive operational product performance. We do this in some of the most advanced and important industries of our time – including Space, Aerospace, Additive Manufacturing, Electric Vehicles, Motorsport, and Renewables. Our work creates positive impact for society, be it by improving the design of artificial hearts, reducing CO2 emissions from aircraft and road vehicles, and increasing the performance of wind turbines.

We are taking the next leap in building out our technology platform and product offering. In this context, we are looking for a capable and enthusiastic research data scientists to join our research team.

This is a hybrid role, meaning you'll enjoy the best of both worlds- flexibility and in-person collaboration. We work together in our NYC office to foster innovation, teamwork and problem-solving. If you're in (or ready to move to) New York and want to be part of a dynamic, hands-on environment, we'd love to hear from you!

Note: We do not provide visa sponsorship in the US. Please only apply if you have the right to work in the US.

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.).
Ideally, >2 years of experience in a data-driven role, 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 optimizing 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

Be part of something larger: Make an impact and meaningfully shape an early-stage company. Work on some of the most exciting and important topics there are. Do something you can be proud of
Work with a fun group of colleagues that support you, challenge you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields and solve truly challenging problems in science and engineering. If you are similarly capable, caring and driven, you'll find yourself at home here
Experience a truly flat hierarchy. Voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo
Work sustainably, striking the right balance between work and personal life.
Receive a competitive compensation and equity package, in addition to plenty of perks

$120,000 - $240,000 a year

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.

PhysicsX Glassdoor Company Review

5.0

PhysicsX DE&I Review

4.8

CEO of PhysicsX

Jacomo Corbo

Approve of CEO

Average salary estimate

$180000 / YEARLY (est.)

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$240000K

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What You Should Know About Research Data Scientist, PhysicsX

At PhysicsX, we're looking for a talented Research Data Scientist to join our innovative team in New York. As a deep-tech company, we specialize in developing cutting-edge machine learning applications that enhance physics simulations, driving optimization in critical industries such as Space, Aerospace, and Renewables. In this hybrid role, you'll collaborate with our diverse team of scientists and engineers, tackling real-world challenges by translating complex physics and engineering concepts into mathematical problem formulations. You will leverage advanced machine learning techniques to build predictive models for physical systems, while also owning research work-streams that align with your expertise. If you're passionate about making a difference—whether it’s improving designs for artificial hearts or reducing emissions from vehicles—you'll find a home at PhysicsX. You’ll not only be encouraged to communicate your findings through various channels but also to mentor junior colleagues and foster a collaborative environment. Plus, you’ll enjoy the best of both worlds with flexible working arrangements. If you have the right to work in the US and a PhD in fields like computer science or physics, we want to hear from you! Join us and be part of a mission that aims to transform engineering processes and drive product performance across numerous sectors.

Frequently Asked Questions (FAQs) for Research Data Scientist Role at PhysicsX

What are the core responsibilities of a Research Data Scientist at PhysicsX?

As a Research Data Scientist at PhysicsX, your core responsibilities will include developing advanced predictive models using machine learning techniques, collaborating with machine learning and simulation engineers to address engineering challenges, and communicating your findings effectively with both colleagues and customers. You'll also mentor junior team members, translating complex concepts into actionable solutions while ensuring that your research directly supports our mission to enhance optimization opportunities in various industries.