Hybrid Materials Scientist - ALD/MLD Research

Hybrid Materials Scientist - ALD/MLD Research

Full-Time 35000 - 45000 £ / year (est.) No working from home possible
Amphiform

At a Glance

  • Tasks: Design and run ALD/MLD synthesis pipelines for innovative materials.
  • Company: Amphiform, a pioneering company in materials science.
  • Benefits: Competitive salary, flexible work environment, and opportunities for research publication.
  • Other info: Collaborative atmosphere with potential for significant career advancement.
  • Why this job: Join a dynamic team and contribute to groundbreaking materials discovery.
  • Qualifications: Strong background in organic synthesis or electrocatalysis with publication experience.

The predicted salary is between 35000 - 45000 £ per year.

Amphiform is seeking a Chemistry/Materials scientist to design and run ALD/MLD synthesis pipelines for organic and inorganic layered materials.

You will work closely with the founding team to develop characterisations and reporting for a closed‑loop materials discovery pipeline.

The role requires a strong background in organic synthesis or electrocatalysis, hands‑on experimental design, and a track record of high‑quality publications in related fields.

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Hybrid Materials Scientist - ALD/MLD Research employer: Amphiform

Amphiform is an exceptional employer, offering a unique opportunity to work at the forefront of energy materials innovation in vibrant London or Oxford. With a strong focus on employee growth and collaboration, you will be part of a dynamic team that values diverse backgrounds and fosters a culture of creativity and scientific exploration. Join us as we scale our operations and make a meaningful impact in the fields of AI, defence, and space.

Amphiform

Contact Details:

Amphiform Recruitment Team

We think you need these skills to ace Hybrid Materials Scientist - ALD/MLD Research

ALD (Atomic Layer Deposition)
MLD (Molecular Layer Deposition)
Organic Synthesis
Electrocatalysis
Experimental Design
Materials Characterisation
Data Analysis