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Scientist, Bio-image Analysis & Operations
Позиция в одной из самых перспективных биотех-компаний Кембриджа с доступом к передовым технологиям. Высокий балл обусловлен инновационностью задач и сильной научной средой, однако отсутствие визовой поддержки ограничивает круг кандидатов.
Сложность вакансии
Роль требует редкого сочетания навыков: глубокого понимания физики микроскопии и продвинутого программирования на Python для анализа данных. Высокая ответственность за дорогостоящее оборудование и необходимость работы в междисциплинарной среде Кембриджского биокластера повышают планку требований.
Анализ зарплаты
Предлагаемая позиция находится в Кембридже, одном из самых дорогих и конкурентных биомедицинских хабов мира. Ожидаемая рыночная зарплата для специалиста такого уровня (Scientist) в Великобритании составляет от £40,000 до £55,000 в год, в зависимости от опыта работы с ИИ и автоматизацией.
Сопроводительное письмо
I am writing to express my strong interest in the Scientist, Bio-image Analysis & Operations position at bit.bio. With a solid background in both advanced microscopy and the development of automated image analysis pipelines, I am eager to contribute to your mission of engineering human cells for the medicine of the future. My experience in managing high-end imaging systems and building robust workflows using Python, napari, and CellProfiler aligns perfectly with the dual nature of this role.
In my previous work within core facility environments, I have successfully bridged the gap between complex hardware operations and high-throughput data processing. I am particularly drawn to bit.bio's commitment to combining synthetic and stem cell biology, and I am confident that my skills in integrating image data with experimental metadata will support your discovery and quality control workflows. I am a proactive problem-solver who enjoys empowering fellow scientists through training and clear communication.
Furthermore, my familiarity with deep learning models like Cellpose and StarDist, along with version control practices using Git, allows me to not only maintain current pipelines but also innovate with AI-driven solutions. I am excited about the opportunity to work at the Babraham Research Campus and contribute to the success of a pioneering company like bit.bio.
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Откликнитесь в bitbio уже сейчас
Присоединяйтесь к bit.bio и создавайте будущее медицины через инновационный анализ биоизображений в Кембридже!
Описание вакансии
bit.bio is an award-winning spinout from the University of Cambridge. Our breakthrough technology combines synthetic and stem cell biology for the precise, efficient and consistent reprogramming of human cells used in research, drug discovery, and cell therapy. At bit.bio, we are passionate about engineering human cells that will enable the medicine of the future. To do this we need talented and curious people who want to make an impact on the future of science and therapeutics.
As a team of individuals, we value science, collaboration, openness, curiosity and creativity. We are united by trust and respect for each other.
Location: Babraham Research Campus, Cambridge
Type: Full time, permanent
Start: Immediate
Salary: Competitive / Hours: 40 p/w
Lab Based Position (Cambridge)
*This role does not meet the minimum salary requirements for UK skilled worker sponsorship. Candidates must already have the right to work in the UK or must not require sponsorship for a Skilled Worker visa.*
Your role in our team:
We are looking for a versatile Scientist with expertise in both advanced microscopy and bio-image analysis to join our Imaging Facility. Reporting to the Imaging Lead within the Automation and Technical Facilities team, you will play a dual role: ensuring our state-of-the-art imaging hardware is performing at its peak and developing the automated analysis pipelines that turn raw pixels into biological insights.
You will work cross-functionally to support the entire bit.bio product workflow, from early-stage discovery to production quality control, ensuring our imaging capabilities remain at the forefront of the industry.
Your key responsibilities will include:
- Imaging Operations: Contribute to the day-to-day maintenance and troubleshooting of the facility’s high-end light microscopy instrumentation to ensure maximum uptime and data quality.
- Workflow Development: Maintain and expand in-house bio-image analysis pipelines. You will assess project requirements, select the appropriate tools, and build automated, well-documented, user-friendly workflows for staff across the organisation.
- Image data integration: Contribute to the development of best-practice workflows to integrate image data with technical and experimental metadata to fuel downstream data models.
- User Empowerment: Provide high-level training and support to scientists on both microscope operation and image analysis software, fostering a culture of best practices in data acquisition and management.
- Automation & Integration: Work with the Automation team to integrate imaging workflows into larger automation and data pipelines, supporting high-throughput phenotyping and QC.
- Documentation & Compliance: Develop and maintain SOPs, risk assessments, and COSHH documentation, ensuring all imaging activities meet health, safety, and data integrity standards.
- Innovation: Assist the Imaging Lead in evaluating and implementing novel imaging technologies and AI-based analysis methods (Deep Learning/Machine Learning) to keep the facility at the cutting edge.
You…
- Will have a minimum Bachelor’s/Master’s degree in a relevant Biological or Physical Science subject (or equivalent experience) with demonstrable industry experience in a core facility or high-throughput imaging environment.
- Possess a "problem-solver" mindset, comfortable with both the physical mechanics of a microscope and the logic of a complex script.
- Are a clear communicator, capable of translating complex image analysis concepts for non-expert end users.
- Are meticulous regarding data integrity, traceability, and documentation.
With essential experience in…
- Advanced Microscopy: Hands-on experience with high-end imaging systems (e.g., confocal, widefield, and high-content screening platforms).
- Open-Source Bio-image Analysis: Proficiency in building and deploying workflows using tools such as Python, napari, Fiji/ImageJ, CellProfiler, or KNIME.
- Pipeline Development: Demonstrated ability to create automated, end-user facing analysis routines that handle large datasets efficiently.
- Data Management: Experience managing large-scale image data and an understanding of bio-image metadata standards.
...and possibly....
- AI/ML Expertise: Experience implementing "off-the-shelf" or custom deep learning models for segmentation, restoration, or classification (e.g., StarDist, Cellpose, Careamics) and/or experience building custom model architectures using PyTorch or TensorFlow.
- Software Engineering: Familiarity with version control (Git) and containerization (Docker) for deploying analysis environments.
- Standardisation: Experience working within a Quality Management System (QMS) or developing validated assays for production QC.
More reasons to join us:
bit.bio provides a vibrant and dynamic work environment in an exciting, fast-moving time for biology. We work with cutting edge technologies and with our world-leading scientific advisory board. We conduct pioneering work with real-world impact.
We trust our people to make significant contributions early on with opportunities to be involved in projects that are key to the success and growth of our young company. We invest in people, creating opportunities for personal development in an inclusive multi-skilled team with ambitious goals that provide opportunities to learn on the job from each other.
Creativity and open minds are encouraged for everyone to contribute to the success of the company.
For information on how we will manage your data please see our Candidate Privacy Notice
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Навыки
- Python
- napari
- Fiji
- ImageJ
- CellProfiler
- KNIME
- PyTorch
- TensorFlow
- Docker
- Git
- Microscopy
- Deep Learning
- Machine Learning
- Image Analysis
Возможные вопросы на собеседовании
Проверка практического опыта работы с оборудованием и способности минимизировать простои.
Опишите ваш самый сложный случай поиска и устранения неисправностей в конфокальном или широкопольном микроскопе. Как вы решили проблему?
Оценка навыков автоматизации и работы с большими данными.
Как бы вы спроектировали автоматизированный пайплайн для обработки терабайтов данных изображений, чтобы сделать его доступным для биологов без навыков программирования?
Проверка владения современными инструментами ИИ в биоинформатике.
В каких случаях вы бы предпочли классические методы сегментации (например, в CellProfiler) глубокому обучению (например, Cellpose), и почему?
Оценка понимания архитектуры данных и метаданных.
Как вы обеспечиваете целостность данных и соответствие стандартам метаданных при интеграции изображений в общие базы данных компании?
Проверка коммуникативных навыков и умения обучать.
Как вы объясните принцип работы сложного алгоритма анализа изображений коллеге-биологу, который никогда не писал код?
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