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From Home Computational Imaging Jobs (NOW HIRING)

Transcripta Bio

Computational Biologist

Palo Alto, CA · On-site

... imaging data. * Analyze data from drug perturbation screens to identify transcriptomic signatures, compound-gene associations, and patterns of drug response across disease-relevant cell models.

Apple

Camera Embedded Software Engineer

Cupertino, CA · On-site

$162K - $213K/yr

... imaging technologies that power hundreds of millions of iPhones, iPads, and Macs around the world. From capturing cinematic video to enabling breakthrough computational photography, we're shaping how ...

Apple, Inc.

Camera Embedded Software Engineer

Cupertino, CA · On-site

$162K - $213K/yr

... imaging technologies that power hundreds of millions of iPhones, iPads, and Macs around the world. From capturing cinematic video to enabling breakthrough computational photography, we're shaping how ...

Apple

Camera Embedded Software Engineer

Cupertino, CA · On-site

$162K - $213K/yr

... imaging technologies that power hundreds of millions of iPhones, iPads, and Macs around the world. From capturing cinematic video to enabling breakthrough computational photography, we're shaping how ...

Apple

Image Scientist - Camera Simulation

Cupertino, CA · On-site

You'll design and develop groundbreaking ideas for everything involved in our camera systems, from ... Optics: imaging system design, Computer Vision, computational imaging, or similar. Experience with ...

Alljoined

Computational Neuroscientist

San Francisco, CA · On-site

$120K - $160K/yr

Our work solves the communication bottleneck between humans and computers by decoding thoughts from ... brain imaging data (EEG, fMRI). * Proficiency in Python (MNE, Numpy, PyschoPy) and associated ...

Brownhealth

Research Assistant

Providence, RI · On-site

$41K - $68K/yr

... computational imaging analysis, machine learning, and prepare figures, technical reports, and ... from all forms of unlawful discrimination and harassment. Location: Rhode Island Hospital - 593 ...

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How much do from home computational imaging jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for from home computational imaging in the United States is $54.93, according to ZipRecruiter salary data. Most workers in this role earn between $46.88 and $73.56 per hour, depending on experience, location, and employer.

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From Home Computational Imaging jobs near you
Infographic showing various From Home Computational Imaging job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, and 4% Contract. Highlights an 79% Physical, 1% Hybrid, and 20% Remote job distribution, with an average salary of $114,249 per year, or $54.9 per hour.

Computational Biologist

Transcripta Bio

Palo Alto, CA • On-site

Full-time

Re-posted 21 days ago

Job description

About Transcripta Bio
Transcripta Bio is a preclinical-stage AI drug discovery company pioneering a patient-first approach to therapeutics. Headquartered in Palo Alto, CA, we have built a proprietary closed-loop discovery engine - comprising our Disease Signature Atlas, Drug-Gene Atlas, and Conductor AI platform - that integrates single-cell patient transcriptomics, causal human genetics, and pre-validated chemistry to identify and advance drug candidates with a structural edge over conventional approaches.
WHAT YOU'LL DO
  • Develop, maintain, and optimize reproducible bioinformatics pipelines for processing, QC, and analysis of high-throughput datasets, including bulk RNA-seq, single-cell RNA-seq, and high-content imaging data.
  • Analyze data from drug perturbation screens to identify transcriptomic signatures, compound-gene associations, and patterns of drug response across disease-relevant cell models.
  • Integrate data across multiple experimental modalities (transcriptomics, imaging, protein measurements) to build a coherent picture of biology and prioritize therapeutic hypotheses.
  • Partner with wet lab scientists to help design experiments, define data standards, troubleshoot data quality issues, and ensure clean handoffs between experimental and computational workflows.
  • Contribute to the curation and expansion of the Drug-Gene Atlas: ensure that data inputs are well characterized, analysis methods are calibrated, and outputs are interpretable and reliable.
  • Communicate findings clearly through reports, visualizations, and presentations to both computational and non-computational colleagues.
  • Stay current with advances in transcriptomics, single-cell methods, and computational biology; evaluate and adopt new tools and approaches where they add value.
  • Contribute to code review, documentation, and best practices as the team grows.

WHAT YOU'LL BRING
  • PhD in Bioinformatics, Computational Biology, Genomics, or a related field with 3+ years of relevant experience in industry.
  • Extensive hands-on experience processing and analyzing bulk and/or single-cell RNA-seq data, from raw reads through QC, normalization, dimensionality reduction, clustering, and differential expression.
  • Experience in relevant scientific packages (e.g., scanpy, pandas, numpy, DESeq2, ggplot2) and comfort working in a Linux/command-line environment. Strong programming proficiency in Python and/or R is a plus
  • Experience building and running reproducible workflows using tools such as Snakemake, Nextflow, or equivalent; familiarity with version control (Git) and best practices for collaborative code development.
  • Exposure to high-throughput or perturbational screening datasets (chemical, genetic, or combined) is highly desirable.
  • A biologically grounded mindset: you approach data with mechanistic questions in mind, not just statistical outputs.

NICE TO HAVE
  • Experience analyzing data from functional genomics assays (e.g., ATAC-seq, ChIP-seq, perturb-seq, or pooled CRISPR screens).
  • Familiarity with spatial transcriptomics or multimodal data integration approaches.
  • Experience working with or alongside ML/AI teams; familiarity with applying machine learning methods to biological data.
  • Background in rare genetic disease, neurodegeneration, or other genetically defined disease areas.
  • Experience in cloud-based compute environments (AWS, GCP, or equivalent)

Apply