Kellton
Imaging Data Scientist
Johnston, Iowa, USA · Contract
Sponsorship not specifiedDetected 104 days ago
PythonCode ReviewGitDeep LearningTensorFlowPyTorchData ScienceNLPComputer VisionStakeholder ManagementMicroscopyLeadershipCommunicationCollaborationPublic Speaking
About the role
- The contractor will contribute to endtoend imaging and analytics from microscopy microspore detection to macroscopic structure assessment and plantlet characterization supporting decisions that reduce cycle time and cost in DH programs.
- Harmonize imaging acquisition with analysis by collaborating with biology teams to standardize microscopy/RGB/hyperspectral capture and file formats (e.g., FIJI/ImageJ for zstacks; autoscale practices).
Responsibilities
- Build productionready pipelines in Python (data ingest, preprocessing, augmentation, inference, batch processing), integrated with GitLab repos and experiment tracking; ensure reproducibility and documentation.
- Implement hyperspectral analysis workflows (band selection, normalization, feature extraction, model training).
- Quantify model performance (precision/recall, F1, ROC/AUC, calibration) and write clear reports/posters for DH sessions; support factchecking in presentations.
- Operationalize at scale: batch processing of tens of thousands of structures/images; optimize inference (e.g., torch.compile, mixed precision) and monitor resource usage.
- Partner with DH stakeholders (biotech & breeding, Genome Technology Discovery, Data Science) to align deliverables with deployment milestones.
- batch processing of tens of thousands of structures/images; optimize inference (e.g., torch.compile, mixed precision) and monitor resource usage.
- Maintain IP & data stewardship practices consistent with internal strategy; avoid disclosure of confidential protocols while enabling model reuse
Requirements
- Proven ability to productionize models: Git/GitLab, code reviews, CICD basics, experiment tracking (MLFlow or equivalent), reproducible data/experiments, and clear documentation.
- Experience with microscopy image processing, multipage TIFFs, zstacks, autoscale/normalization, and image quality challenges.
Benefits
- NicetoHave Vision Transformers (ViT) and modern YOLO workflows for microscopy/macroscopic tasks; comfort with infer tooling.
- Curious and learning mindset Technical leadership experience
- Design & deliver deep learning-based CV models for microscopy and macroscopic assays (detection, segmentation, classification) with measurable accuracy, robustness, and throughput.
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