Scientist I, Deep Learning and Computer Vision – Cell Science

The mission of the Allen Institute for Cell Science is to create multi-scale visual models of cell organization, dynamics, and activities. Our approach encompasses large scale data collection, observation, theory, and predictions to understand cellular behavior in normal and pathological contexts. As a division within the Allen Institute, the Allen Institute for Cell Science uses a team-oriented approach, focusing on accelerating foundational research, developing standards and models, and cultivating new ideas to make a transformational impact on science.

The Allen Institute for Cell Science uses 3D live cell imaging to generate unprecedented data for the analysis of the cell and its components as an integrated system. We seek a talented scientist to join the Computational Biology and Machine Learning Team to help build, analyze, and deploy sophisticated computational models of cell states and dynamic cellular processes that leverage these rich images and movies independently and in concert with diverse complementary data. Research at the Institute is highly collaborative, requiring scientists and engineers to work across disciplines, focusing on high impact biological questions and establishing/maintaining the highest standards for best practices and computational rigor.

The role of this position is to develop, implement and apply deep neural networks to identify and understand patterns in Institute-generated high content, live cell microscopy images and time-lapse movies. Examples of current machine learning projects in the team include: prediction of subcellular structures from transmitted light microscopy (see here), and building an integrated model of subcellular structure using a conditional generative model (see here).

The Allen Institute believes that team science significantly benefits from the participation of diverse voices, experiences, and backgrounds. High-quality science can only be produced when it includes different perspectives. We are committed to increasing diversity across every team and encourage people from all backgrounds to apply for this role.

**Applicants should include a brief cover letter (max 1 Page) summarizing relevant research experience and qualifications.

Essential Functions

• Conceive, develop, and implement machine learning models to analyze live cell microscopy images
• Train, parametrize, and evaluate machine learning models to elucidate cellular organization and cell state transitions
• Promote integration and sharing of tools, resources, models, and data across the Institute
• Work across teams to transform prototype models into professionally packaged and reusable applications with intuitive and accessible visualizations
• Practice software development best practices and follow industry standards
• Communicate effectively within and across teams, as well as with the greater scientific community through presentations, documentation, web dissemination, and research papers
• Actively seek and develop creative solutions for problem solving and standardization

Note: Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. This description reflects management’s assignment of essential functions; it does not proscribe or restrict the tasks that may be assigned.

Required Education and Experience

• PhD in computational biology, bioinformatics, machine learning, statistics, applied mathematics, computer science/electrical engineering, or related field or equivalent combination of degree and experience is required
• Experience implementing and applying machine learning models, specifically deep learning approaches, to biological image data, using Python
• Command of current machine learning literature
• Experience using common computational biology methods, tools, and data resources
• Demonstrated success working on interdisciplinary projects
• Demonstrated proficiency in scientific computing including Python and Linux/UNIX environment 
• Experience utilizing software engineering practices such as version management, build management and testing

Preferred Education and Experience

• Comfortable designing and sharing their own scientific computing stack
• Knowledge of image-processing and/or image analysis applications
• Able to provide expertise on a range of scientific computing problem settings, including application of appropriate models and data requirements
• Experience implementing and applying machine learning models with PyTorch
• Familiarity with high-throughput biological data
• Strong communication skills and ability to work in a collaborative, multi-disciplinary environment

Physical Demands

• Fine motor movements in fingers/hands to operate computers

Position Type/Expected Hours of Work

• This role is currently able to work remotely due to COVID-19 and our focus on employee safety. We are a Washington State employer, and remote work must be performed in Washington State. We continue to evaluate the safest options for our employees. As restrictions are lifted in relation to COVID-19, this role will return to work onsite.

Additional Comments

• **Please note, this opportunity does not sponsor work visas**
• **Please note, this opportunity offers relocation assistance**