Biomaterials Scientist

Sava
London
10 months ago
Applications closed

Join to apply for theBiomaterials Scientistrole atSava

Company Information
All the health information we need is within us. Just below the skin. SAVA is redefining the way people interact with their health by developing the most advanced biosensing technology science has to offer, capable of accessing bodily information in a painless, real-time and affordable way.

Description
We are looking for a Senior/Scientist to join the Biomaterials Team, within the Biosensing and In Vivo Performance Department. The selection and optimisation of the materials used in our sensors is of utmost importance for device performance and longevityin vivo. The ideal candidate will bring experience in materials characterisation, and an in-depth understanding of how various properties will impact the material-tissue interface, and so the function of the biosensor as a whole.

Responsibilities

  • Work within the Biomaterials Team to develop and characterise the materials being utilised in all aspects of a minimally invasive biosensor platform.
  • Collaborate with the Chemistry, Process, and Manufacturing teams to implement material changes for optimisation of sensor performance, longevity and safety.
  • Develop new protocols to further the understanding of various aspects of sensor composition and performance.
  • Utilise analytical techniques to understand how material characteristics impact sensor manufacturing and device function.
  • Coordinate testing to determine the biocompatibility of novel candidate materials.
  • Generate, analyse and report data to the team and wider company, verbally and in writing.
  • Maintain detailed, up to date records of experiments and data analysis.
  • Research and source new equipment to support critical research areas.
  • Liaise with internal and external stakeholders to coordinate projects, managing deadlines and requirements in parallel to advance device development.

Past Experience

Essential:Masters degree plus > 2 years lab experience post-graduation in a relevant discipline (e.g., materials science, bioengineering, tissue engineering), working with materials development and characterisation.

Preferred:PhD in a relevant discipline (e.g., materials science, bioengineering, tissue engineering), working with materials development and characterisation. Industry experience post-PhD would be beneficial.

Requirements

  • Multidisciplinary background is advantageous, given the requirements of this role. The candidate will be expected to work across departments, interacting with scientists, engineers, Operations, external suppliers and regulatory bodies.
  • Comfortable being hands on in the lab, and can demonstrate a degree of independence and ownership of work.
  • Adaptability - this role requires the ability to learn new skills and techniques quickly, and to deal with the fast pace of a startup environment.
  • Materials characterisation and/or biomaterials experience, which may include: mechanical characterisation, rheology, material hydration studies, hydrogel processing and characterisation, analyte diffusivity, cell or tissue culture, cell/material interfacing, bioactive materials, enzyme stability and activity, protein conjugation and characterisation, colorimetric or fluorescence-based assays, microscopy, SEM/EDX.
  • Experimental design - organisational skills and attention to detail.
  • Presentation and communication of data to both technical and non-technical audiences.
  • Excellent interpersonal and communication skills.

Preferred

  • Experience with biological systems preferred (but not essential, as long as proficiency with the different techniques required can be demonstrated).
  • Experience with and knowledge of biosensors or medical devices with skin/surface interaction.
  • Experience with ISO 10993 or other appropriate regulatory standards and biocompatibility testing methods.
  • Experience with data analysis and visualisation software (e.g., python, R, MATLAB).

Sava Technologies Ltd is an equal opportunity employer. We consider candidates regardless of age, ancestry, colour, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third-party affiliation, sex, pregnancy, sexual orientation, gender identity, or military or veteran status.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Other

Industries

IT Services and IT Consulting

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.