ML Scientist

CellVoyant
Bristol
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Scientist

Director, Research & Labs, Data Standards and Excellence

Director, AI & Advanced Analytics

We are actively searching for a highly motivated and skilledMachine Learning scientistproficient in ML and computer vision, with a keen interest in genomics, microscopy data and their applications. As a Machine Learning scientist, your role will be pivotal in advancing the development of ourAI models. This encompasses contributions to research, methodology development, data enhancement, and collection. You will be at the forefront of driving innovation in research and development at CellVoyant, leading to groundbreaking discoveries and creating new opportunities forpioneering research and publications.

Requirements

As a ML Scientist you will be at the forefront of shaping the CellVoyant AI development with a focus on leveraging computer vision for microscopy data and collaborating closely on genomics-related projects. Your primary responsibilities include:

  • Pioneering Research Advancements: Identifying and leveraging state-of-the-art research papers and cutting-edge methodologiesin machine learningto drive innovation in our AI modelsenabling predictive modelling, detection, classification, and pattern recognition of stem cell populations.
  • Data Enrichment: Identifying and sourcing open-source multi-modal data sets,(e.g., genomics and microscopy imaging), to enhance the robustness of our AI models. This involves collaborating closely with computational biologists to ensure data relevance and quality.
  • Data Strategy and Proof of Concept: Strategically identifying essential data requirements and developing data collection approaches to validate proof of concept for our AI models, particularly in the context of microscopy data analysis and genomics-related hypotheses.
  • Collaboration and communication: Collaborate with cross-functional teams, includingcomputational biologists,biologists, data scientists, and software engineers, to drive multidisciplinary research projects.This involves fostering strong communication channels to effectively integrate computer vision techniques into genomics research endeavors.

Qualifications:

    • A strong track record of research publications intop-tier AI conferencessuch as NeurIPS, AAAI, ICLR, ICML, CVPR, ECCV, IJCV.
    • Ph.D. degree in a technical subject (e.g. machine learning, AI, computer science, mathematics, physics, statistics).
    • Proficiency in programming languages like Python, cloud infrastructure (e.g., Google Cloud) and experience with relevant software (e.g., Github, Docker).
    • Knowledge of ML/scientific libraries such as TensorFlow, PyTorch, NumPy and Pandas.
    • Excellent analytical, problem-solving, and critical-thinking abilities.
    • A collaborative mindset and the ability to work closely with computational biologists to identify hypotheses and validate proof of concept are essential for success in this role
    • Experience with Large-Scale System Design
    • Expertise in Self-Supervised ML and Generative Models such as Auto-encoders and GANs (Generative Adversarial Networks).
    • Familiarity with Advanced Decision-Making Approaches: such as Deep Reinforcement Learning (DRL), Imitation Learning (IL), and learning from demonstrations.
    • Expertise in Multi-Task and Multi-Modal Learning
    • Proficiency in Sequential Models such as Transformers.

Nice-to-have skills or background

    • (A big plus) Experience in genomics or bioinformatics research projects in an academic, pharmaceutical, or biotechnology setting.
    • (A big plus) Experience in microscopy data and their applications
    • Proven experience in stem cell research projects in an academic, pharmaceutical, or biotechnology setting.

Benefits

  • Join at the ground level to work at the cutting-edge of artificial intelligence, stem cell biology, empirical experiment automation, and cell therapy development, enabling groundbreaking research and publication opportunities.
  • Help us build our company culture and create an inclusive, collaborative and intellectually stimulating culture that puts science at the forefront of everything we do.
  • Join a dynamic, diverse, and inclusive team of experienced and interdisciplinary scientists applying their skills to some of the most impactful problems in human health, to make a long lasting positive impact on society.
  • Ability to work remotely or in our Bristol, UK headquarters and join bi-annual week-long company off sites.

 

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 Biotechnology Job Applications (UK Guide)

Hiring managers in biotechnology do not start by reading your CV word for word. They scan for credibility, relevance and risk. In a regulated, evidence-driven sector like biotech, the first question is simple: is this person safe, competent and genuinely capable of contributing in this environment? Whether you are applying for roles in research, manufacturing, quality, regulatory, clinical, bioinformatics or commercial biotech, the strongest applications make the right signals obvious in the first 10–20 seconds. This in-depth guide explains exactly what hiring managers in UK biotechnology look for first, how they assess CVs, cover letters and portfolios, and why capable candidates are often rejected. Use it as a practical checklist before you apply.

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

Biotechnology sits at the intersection of science, innovation and real-world impact. From life-saving medicines and diagnostics to sustainable agriculture, industrial bioprocessing and personalised healthcare, biotech plays a critical role in the UK economy. Yet despite strong graduate numbers and world-class universities, employers across the biotechnology sector continue to report a growing skills gap. Vacancies remain unfilled. Graduates struggle to secure their first roles. Hiring managers cite a lack of job-ready candidates. The issue is not intelligence or academic ability. It is preparation. Universities are producing scientifically knowledgeable graduates who are often not ready for modern biotechnology jobs. This article explores the biotechnology skills gap in depth: what universities teach well, what is missing from many degrees, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build sustainable careers in biotech.

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.