Polymer Synthesis Lead at Cambrium

Paris, Ile-de-France, France -

Full Time

Start Date

Immediate

Expiry Date

10 Aug, 26

Salary

0.0

Posted On

13 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Polymer Synthesis, Polymer Physics, Chemical Engineering, Step-growth Polymerization, Lab Commissioning, High-throughput Synthesis, GPC, DSC, DMA, Rheology, FTIR, Mechanical Testing, LIMS, ELN, Block Copolymers, ML-ready Data

Industry

Description

What we do Cambrium is a molecular intelligence company engineering advanced materials that outperform. From personal care to textiles, mobility to home care, we design and manufacture materials that deliver real results today and for generations to come. Our platform brings together molecular intelligence and living systems to design and produce enzymes, polymers, and peptides at scale, unlocking performance characteristics that traditional chemistry could never access. Within polymers specifically. Our stack: we design enzymes that produce novel monomers, then combine them into block copolymers that break through the performance tradeoffs of existing polymers. We have done this once already, and now we're making it systematic. Polymers today are where proteins were before AlphaFold: the architectures exist, the training data doesn't. We're building the lab and the dataset that changes that. We are an equal-opportunity employer and value diversity. We consider all applications equally regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply, and we can help with immigration. Your role We are building a polymer synthesis and characterization lab from zero: parallel reactors, automated characterization, and the throughput to generate thousands of datapoints per month. This lab is the data engine behind our polymer AI foundation model. Someone needs to build it, commission it, and run it. You are the first wet-lab hire for our polymer AI lab. You will lead the physical lab: reactor procurement, characterization stack, synthesis protocols, and the ramp from first experiment to steady-state throughput. You collaborate daily with the Head of Polymers and the CTO. A computational chemist is being hired in parallel to lead the compute track. You two are the two co-architects of this new segment. Your Responsibilities Lead lab buildout end-to-end: site preparation, equipment procurement, installation, commissioning Set up the characterization stack for molecular weight, thermal, mechanical, rheological, and chemical properties Design and validate synthesis protocols for block copolymer families using bio-based monomers produced by our enzyme platform Build the sample-to-datapoint pipeline: from reactor output through characterization to structured, ML-ready data Ramp throughput from first experiments to thousands of datapoints per month at steady state Grow and mentor the synthesis team as the lab scales Collaborate with the computational chemist to close the active learning loop: the model suggests what to synthesize next, you make it happen and feed back results Inform reactor expansion decisions based on verified yield data Your profile PhD and 5+ years of experience in: Polymer chemistry, polymer physics, or chemical engineering with a strong polymer synthesis focus Hands-on experience with step-growth polymerization (polycondensation, polyaddition). You've synthesized polymers, not only characterized them Experience building or commissioning a chemistry lab, or leading a significant lab expansion. You know what it takes to go from an empty room to running experiments Familiarity with parallel or high-throughput synthesis platforms. Experience with multi-reactor setups is important for this role Working knowledge of polymer characterization techniques: GPC, DSC, DMA, rheology, FTIR, and mechanical testing. You don't need to be a specialist in all of them, but you should know what each measurement tells you and when to trust it Experience working with data systems (LIMS, ELN, or structured experimental records). We're building an AI training dataset, not a lab notebook collection Strong signals: Experience with block copolymers specifically (phase separation, microphase morphology, structure-property relationships) Background in bio-based or sustainable polymers, including the monomer purity and feedstock variability challenges that come with them Experience with automation or semi-automated synthesis workflows Previous work in an environment where experimental data fed directly into ML models. You understand what "ML-ready data" means in practice Track record of growing a lab operation: hiring, managing throughput, optimizing cost per experiment Prior industry experience at a polymer company, coatings manufacturer, or materials startup What we offer Employee Stock Options Flexible working hours Learning & Development Programme for all our team members Build a lab from scratch with real budget and a clear mission, not a retrofit or an afterthought Your data trains a foundation model. Every datapoint you generate makes the AI better, and the AI tells you what to make next. This is the tightest experiment-to-model loop in polymer science Gym membership Subsidised lunch and impassioned lunch discussions 30 days of individual vacation plus up to 5 all-company holidays between the 25th of December and 1st of January Regular team events Be part of our journey to a future of advanced materials that outperform

Responsibilities

Lead the end-to-end buildout and operation of a polymer synthesis and characterization lab to generate data for an AI foundation model. Collaborate with computational chemists to implement an active learning loop for novel block copolymer development.