Arcadia – seeking Scientist, Image Analysis

We are Arcadia Science. Arcadia is a science company founded and led by scientists. Our mission is to transform evolutionary innovations into real-world solutions by openly developing more efficient, replicable, and sustainable ways to leverage the biology of diverse organisms.

The Opportunity:
We are seeking a highly collaborative and motivated scientist who is excited about statistical analysis of microscopy data and generating computational tools for biologists. With this hire, we plan to expand functionality in high-content image analysis and expand the predictive capacity of novel features from multi-modal data types. We are looking for someone who enjoys working in a team environment and responds well to the fast pace and iterative nature of experimental work. Enthusiasm for open science is required as we publish our work in smaller units, quickly, and iteratively.
The overarching goal of the Microscopy Team’s efforts at Arcadia is to enable discovery across the tree of life using label-free image-based experimental approaches. As a part of Arcadia’s Discovery Platform, we are pursuing tools and approaches that are highly adaptable and scalable as we build capacity for high-content imaging experiments across a wide range of organisms. Our Team aims to iterate on existing tools and build flexible pipelines for image processing and statistical analysis that will be deployed  for different experimental needs, whether that is through collaboration with scientists at Arcadia or shared openly in the broader community.
We believe there is untapped potential to extract quantitative information from data-rich videos of live organisms moving in 3D over time. Whether we are working with datasets generated in-house or from open-source data, our goal is to be able to input largely label-free images (DIC/Phase/autofluorescence), quickly get a sense of the distribution of data on many features in the image, and robustly test hypotheses through statistical analysis.
Within 3 months, you should be able to develop computational pipelines that input raw microscopy data and process the data appropriately, extract quantitative metrics, and statistically evaluate the signal. You should feel ready to implement specific statistical analyses to evaluate the composition of high-resolution images in terms of fine features, volumes of specific shapes and sizes, and identify other signatures without a priori knowledge. You should be able to implement comparative analyses of the morphology and motility of cells/organisms from video data.
Within the first 6 months, you may also enable new imaging approaches by combining computational algorithms with collecting different types of microscopy data. You may employ machine-learning models to analyze imaging data in high-throughput ways. Throughout this time, you will be solving analysis problems for different projects and collaboratively writing short publications on this work.
If you are a curious person with programming and analytical skills that sound complementary to these types of data, and have a strong background in statistical analysis, please review the responsibilities and answer the questions below.


    • Designing and implementing computational pipelines for processing of biological data from microscopy images
    • Applying appropriate statistical analysis methods for biological data
    • Processing and analyzing high-content microscopy images especially those that are label-free and high-throughput
    • Collaborating with biologists and integrate user-feedback into the processing/analysis pipelines
    • Communicating readily at different levels of technical expertise
    • Applying statistical rigor to a variety of data
    • Helping to design figures and write pubs

Education/Experience (Required)

    • PhD in Computational Biology, Bioinformatics, Applied Math, Biology, Biomedical Engineering or a related field.
    • Experience in image processing and scientific programming in Python (e.g. NumPy, SciPy, scikit-image, PyTorch, etc) and/or R, or MATLAB.
    • A strong background in statistical analysis, ideally with biological data (e.g. multivariate models, waveform analysis, Fast Fourier Transform and spectral analysis, denoising and deconvolution algorithms).

Education/Experience (Preferred)

    • A strong background in image processing including segmentation, object identification, quantification, and feature extraction.
    • Experience in computational imaging and image reconstruction algorithms (e.g. quantitative phase, Fourier ptychography).
    • Experience with fluorescence microscopy, brightfield microscopy, DIC, phase, or other.
    • Experience with video data as well as 3D stacks of images.
    • Experience building, maintaining, and using large-scale datasets.
    • Excellent interpersonal and project management skills.
    • Excellent written and oral communication skills.
Successful applicants can expect to be compensated between 125-150K with benefits and a highly competitive equity offering, depending on experience level. The scientist is part of the microscopy team, and reports to Tara Essock-Burns. The position will require the individual to be on-site at our Berkeley, California headquarters.
Application Process: Interested applicants should send a resume and a one-page cover letter that addresses their interest and qualifications for the position.
Arcadia Science is an equal opportunity workplace; we welcome people from all backgrounds and communities. We provide competitive compensation and practical benefits to keep you happy and healthy so that you can do your best work.
Please note that an offer of employment from Arcadia is contingent upon the successful clearance of a reference and background check.
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