Computational Designer — Hybrid Living Textiles
OXMAN· Design· Jul 14, 2026 · 4mo agoPosted 105 days ago
NYC Office
In office
Full-time
Mid
$125K–$157K
Before you apply
Ghost Signal:
Open since July 14, 2026 — 105 days, and still accepting applications.
Job description
OXMAN
OXMAN is a hybrid Design and R&D company that fuses design, technology, and biology to invent multi-scale products and environments. We reject the human-centric design paradigms that have divorced us from Nature, and instead pursue a Nature-centric approach—delivering solutions by, for, and with the natural world. We design across scales for systems-level impact, treating every construct as a whole system of complex interrelations rather than an isolated object.
ROLE OVERVIEW
OXMAN seeks a Computational Designer to advance our work around Textile Design and Hybrid Living Materials. This person sits at the intersection of computational design, textile engineering, and synthetic biology, developing the algorithmic processes, predictive models, and automated fabrication systems through which living and engineered matter are woven together. They are fluent in code and at home in at least one of textile craft or biological reasoning—and curious enough to work across all both, treating computation as a language for mediating between digital design intent, material behavior, and biological agency.
The role spans three integrated levels: the computational design of textiles themselves; the modeling of biological behavior that plays on across those textiles; and the engineering and automation of the fabrication processes that produce them. We're looking for genuine depth in one or two, an appetite for the rest, and the instinct to translate between them.
KEY RESPONSIBILITIES
- Build pipelines that translate computational designs into machine instructions.
- Model and predict complex behavior—deformation, drape, stability, and structural response—for simulation and design optimization.
- Develop mechanistic, dynamical, or data-driven models of biological processes (pattern formation, growth, multicellular signaling, genetic circuits).
- Use computation to narrow large combinatorial possibility spaces.
- Collaborate with a multidisciplinary team of engineers, biologists, and designers, translating ideas and methods across domains.
- Communicate work clearly through meetings, presentations, and creative outlets, and maintain a shared library of processes, models, and tools.
PREFERRED EXPERIENCE
These are the three areas the role works across. Strong candidates will bring depth in one or more and the curiosity to engage with the others.
Computational textile design
- Develop computational processes for knit and weave design, including parametric and generative methods for structure, pattern, and form.
- Build pipelines for the translation of computational designs into machine instructions (knit programming, jacquard instruction sets), closing the gap between geometry and fabrication.
- Develop inverse-design methods that derive machine instructions from target geometries or performance specifications
- Model and predict textile behavior—deformation, drape, stability, and structural response—to enable forward simulation and design optimization.
Modeling biological behavior
- Build mechanistic and data-driven models of the biological processes that play out on and through textile substrates—genetic-circuit and gene-regulatory dynamics, and spatial pattern formation, growth, and multicellular signaling—moving fluently between deterministic (ODE) and stochastic formulations, and between first-principles models and ML as each problem warrants.
- Calibrate and constrain these models against experimental data: parameter inference, sensitivity and identifiability analysis, and model-guided design of experiments.
- Use computation to narrow large combinatorial possibility spaces—screening which biological and material configurations are worth realizing in vivo rather than over-specifying systems in silico.
- Characterize and improve the stability and repeatability of living-material outcomes, building predictive models robust to biological and process variation
- Maintain a critical, empirically grounded stance on where modeling adds value and where physical experimentation leads.
Process engineering & automation
- Augment living-textile fabrication through design engineering and automation—programming robots, and knitting/weaving platforms
- Design and integrate sensor systems and controllers for closed-loop monitoring and control of hybrid living-material processes.
- Build tooling and infrastructure that make experimental processes reproducible, instrumented, and scalable across the digital–physical–biological domains.
TECHNICAL SKILLS
Depth in one or more of the following areas
Computational textile design:
- Computational design tools (for example:Rhino, Grasshopper)
- Knit/textile programming environments (KnitPaint, Stoll M1 Plus, Shima Seiki APEX); hands-on experience with CNC knitting machines (STOLL and/or Shima Seiki) and/or industrial jacquard looms
- A strong grasp of the physics and mechanics of knitted and woven textiles, fibers, and deformation.
Biological modeling:
- Mechanistic and/or data-driven modeling of biological or physical systems—ODE/stochastic models of genetic circuits and gene-regulatory networks, kinetic modeling, or machine learning for prediction and generative/inverse design
- Working fluency in biological reasoning sufficient to collaborate substantively with synthetic biologists (familiarity with combinatorial assembly, multicellular behavior, or microbial systems a plus).
Process engineering & automation:
- Robotics, CNC, sensing, and control systems—programming, integration, and closed-loop automation of fabrication processes.
ESSENTIAL QUALITIES
- Strong programming ability.
- A genuinely cross-disciplinary instinct: able to translate ideas, methods, and constraints between design, engineering, and biology, and to collaborate substantively with specialists outside your own area
- A strong "maker" mindset—rigorous, empirical, and self-critical about where modeling adds value versus where you should simply build and test
- Portfolio demonstrating original computational work and out-of-the-box thinking
- Excellent written and verbal communication; commitment to the team and to ethics and integrity in all work
Application prep
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Keywords to mirror
restmlmachine learning
- Platform
- ashby
- Effort
- quick