* Develop and Maintain the Fractal Platform
o Contribute to the development and enhancement of the Fractal platform for large-scale bioimage analysis, ensuring it adheres to community-agreed open standards for image storage and visualization.
* Convert Microscopy Image Formats
o Implement efficient methods for converting diverse microscopy image formats into the OME-Zarr format to enable standardized storage and accessibility.
* Integrate Image Processing Algorithms
o Wrap image processing tasks such as Cellpose, optimizing performance for both CPU and GPU architectures.
* Design Scalable Task Architectures
o Contribute to creating flexible and scalable task architectures capable of running on HPC-like computing backends to handle large-scale image analysis.
* Develop Web-Based GUIs
o Build and refine user-friendly web-based graphical interfaces to start workflows, visualize data, and navigate data structures effectively.
* Collaborate with Bioimaging Experts
o Work closely with bioimaging experts and stakeholders to ensure that developed tools align with current and future imaging needs in bioimage analysis.
* Implement Workflow Automation
o Design automated workflows for large-scale bioimage analysis, minimizing manual intervention while ensuring reproducibility and accuracy.
* Optimize Performance for Large Datasets
o Identify and implement strategies to handle and process large bioimage datasets efficiently while maintaining data integrity.
* Adopt and Contribute to Open Standards
o Ensure that tools and workflows are compatible with community-agreed standards, and contribute to the development of these standards where applicable.
* Enable Seamless Data Sharing
o Develop features to facilitate seamless data sharing and integration across different imaging platforms and tools.
* Perform Software Testing and Debugging
o Conduct thorough testing and debugging of image analysis software to ensure reliability, accuracy, and performance across diverse datasets.
* Document and Share Technical Insights
o Create and maintain comprehensive technical documentation for developed tools and workflows, fostering knowledge sharing and collaboration within the bioimaging community.
Requirements
* Degree in Relevant Field
o A degree in bioinformatics, computer science, mathematics, or a related discipline is required to ensure a solid theoretical foundation for bioimage analysis and software development.
* Proficiency in Scientific Python
o Strong skills in Python, specifically for scientific computing, are essential for developing bioimage analysis software and implementing algorithms.
* Experience with Relevant Frameworks and Tools
o Familiarity with key frameworks and tools used in scientific Python development, such as NumPy, SciPy, TensorFlow, and others relevant to bioimage analysis, is a must.
* Software Engineering Practices
o Proficiency in software engineering tools and methods, including source control (GitHub/GitLab), CI/CD pipelines, and containerization (Docker), to ensure robust and reproducible software development.
* Experience with Cloud or HPC Environments
o Strong experience in designing scalable software solutions that can leverage high-performance computing (HPC) environments or cloud-based infrastructures for large-scale image processing tasks.
* Mathematics and Statistical Knowledge
o Solid understanding of mathematics, exploratory data analysis (EDA), and statistical methodologies is required to analyze bioimage data accurately and to implement advanced image processing algorithms.
* Familiarity with Bioimage Analysis Techniques
o Knowledge of or experience with common bioimage analysis techniques, including image segmentation, object detection, and feature extraction, particularly for microscopy data.
* Proficiency in Data Storage Standards
o Familiarity with data storage formats such as OME-Zarr, HDF5, or other bioimage standards, and understanding how to efficiently store and retrieve large image datasets.
* Experience with GPU and Parallel Computing
o Proficiency in utilizing GPU and parallel computing techniques to accelerate image processing tasks, particularly for handling large datasets.
* Problem-Solving and Analytical Thinking
o Strong problem-solving skills and the ability to think analytically to develop efficient and effective solutions for bioimage analysis challenges.
* Cross-Disciplinary Collaboration Skills
o Ability to work collaboratively with biologists, clinicians, and other stakeholders to understand requirements and implement solutions that meet the needs of diverse users.
* Strong Communication Skills
o Strong verbal and written communication skills to document software, write technical reports, and present findings or solutions clearly to both technical and non-technical audiences.
What we offer
* B2B Contract
o Employment based on a B2B contract.
* Stable and Dynamic International Firm
o Opportunity to work in a stable, dynamically developing international company.
* Engaging Projects and Latest IT
o Chance to participate in interesting projects and work with the latest information technologies.
* Competitive Rates
o Attractive remuneration rates offered.
* Renowned International Projects
o Involvement in the most prestigious international projects.
* Multisport and Private Medical Care
o Access to Multisport benefits and private healthcare services.
Nice to have
* Experience with Image Processing on Biological Datasets
o Previous experience applying image processing techniques specifically to biological datasets, with an emphasis on microscopy images, is highly preferred to ensure familiarity with the challenges of biological data analysis.
* Development of User-Facing Applications
o Experience in developing user-facing applications, either with Python (e.g., using frameworks like Flask/Django) or web technologies (JS/HTML/CSS), is beneficial for building intuitive interfaces for bioimage analysis.
* Knowledge of Deep Learning Methods
o Familiarity with deep learning methods, particularly those used for image segmentation, object detection, or other image processing tasks, is a plus for leveraging state-of-the-art techniques in bioimage analysis.
* Knowledge of Classical Machine Learning Methods
o Understanding classical machine learning methods, such as clustering, classification, and regression, which can be applied to bioimage data analysis for extracting insights or automating processes.
* Experience with Image Processing Libraries and Frameworks
o Experience with specialized image processing libraries, such as OpenCV, scikit-image, or Cellpose, is highly advantageous for efficiently developing and deploying image analysis workflows.
Work with us
Apply & join the team
Didn’t find anything for yourself? Send your CV to praca@seargin.com
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