Machine Minder

Colchester
9 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Director, AI/ML/Advanced Analytics, Automation & Digital Agent CoE

Associate Director, AI & Advanced Analytics

Senior Mechatronics Engineer

Process Technician (Inspection and Packaging)

Our client are a leading manufacturer of Pharmaceutical Products, you will be required to work on a 12 hour shift pattern of nights and days throughout the year, this will include weekends and Bank Holidays as part of your normal working week.

You will work for 3 night shifts then have 3 days off, you will then work for 3 days then have 6 days off, this pattern rotates ongoing through out the year.

Your pay rate is £12.39phr for both day/night shifts, once trained if you complete more than 12 shifts in any month any further shifts will get paid at overtime rate of time and a half.

The client requires that you have some previous, manufacturing maching minding experience for this position, also some previous use of hand tools is preferable.

if you are interested please give us a call now to disucss this position further

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.

Biotechnology Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Biotechnology is often portrayed as a young person’s game. White lab coats, fresh PhDs & long academic pipelines dominate the image. In reality, the UK biotechnology sector relies heavily on career switchers, mid-career professionals & people bringing experience from outside science. If you are in your 30s, 40s or 50s & thinking about moving into biotechnology, this article gives you a clear-eyed, UK-specific reality check. No hype. No Americanised career myths. Just an honest look at which biotech jobs are realistic, what retraining actually involves & how employers really think about age & background.

How to Write a Biotechnology Job Ad That Attracts the Right People

Biotechnology is one of the UK’s most diverse and fast-moving sectors. From biopharma and diagnostics to industrial biotech, medtech and life sciences research, employers are competing for highly specialised talent with scarce, in-demand skills. Yet many biotechnology employers struggle with the same problem: job adverts that attract the wrong candidates. Roles are often flooded with unsuitable applications, while highly qualified scientists, engineers and regulatory professionals either do not apply or disengage early in the process. In most cases, the issue is not the talent pool — it is the job advert itself. Biotechnology professionals are trained to think critically, assess evidence and understand context. If a job ad is vague, inflated or poorly targeted, it signals a lack of clarity and credibility — and strong candidates simply move on. This guide explains how to write a biotechnology job ad that attracts the right people, improves applicant quality and positions your organisation as a serious, trustworthy employer in the life sciences sector.

Maths for Biotech Jobs: The Only Topics You Actually Need (& How to Learn Them)

Biotechnology is packed with data. Whether you are applying for roles in drug discovery, clinical research, bioprocessing, diagnostics, genomics or regulated manufacturing, you will meet numbers every day: assay readouts, QC trends, dose response curves, sequencing counts, clinical endpoints, stability profiles, validation reports & risk assessments. If you are a UK job seeker moving into biotech from another sector or you are a student in biology, biochemistry, biomedical science, pharmacy, chemistry, engineering or computer science, it is normal to worry you “do not have the maths”. What biotech roles do need is confidence with a small set of practical topics that show up again & again. This guide focuses on the only maths most biotech job adverts quietly assume: • Biostatistics basics for experiments, evidence & decision making • Probability for variability, uncertainty & risk • Linear algebra essentials for omics, PCA & modelling workflows • Calculus basics for kinetics, rates & dose response intuition • Simple optimisation for curve fitting, process set points & model tuning