Biomedical Image Analysis Scientist
Join us and contribute to the discovery of medicines that will impact lives!
About Aganitha
Accelerate drug discovery and development for Biopharma and Biotech R&D with in silico solutions leveraging Computational Biology & Chemistry, High throughput Sciences, AI, ML, HPC, Cloud, Data, and DevOps.
In silico solutions are transforming the biopharma and biotech industries. Our cross-domain science and technology team of experts embark upon and industrialize this transformation. We continually expand our world-class multi-disciplinary team in Genomics, AI, and Cloud computing, accelerating drug discovery and development. What drives us is the joy of working in an innovation-rich, research-powered startup bridging multiple disciplines to bring medicines faster for human use. We are working with several innovative Biopharma companies and expanding our client base globally. Read about how and what solutions we build.
Aganitha (अगणित): “countless” or “limitless” in Sanskrit serves as a reminder and inspiration about the limitless potential in each one of us. Come join us to bring out your best and be limitless!
Key Responsibilities
- Design, implement, and optimize algorithms for biomedical image analysis using deep learning and computer vision techniques (CNNs, transformers, diffusion models, etc.).
- Work on multi-modal datasets — including cellular images, microscopy, MRI, CT, EEG, ECG and histopathology slides — to extract meaningful biological or clinical insights.
- Develop automated image & waveform segmentation, classification, and feature extraction workflows.
- Collaborate with biologists, chemists, and AI engineers to integrate imaging data with omics and molecular datasets.
- Contribute to building scalable pipelines for image data preprocessing, model training, and deployment.
- Validate models against experimental data and ensure reproducibility of results.
- Stay current with advances in biomedical imaging, AI/ML architectures, and data integration methods.
Required Skills & Experience
- Strong background in Biomedical Engineering, Computer Science, Electrical Engineering, Biophysics, Computational Biology, or related field.
- PhD or Master’s degree with experience in biomedical image analysis or computer vision.
- Hands-on experience with Python, PyTorch (or TensorFlow), OpenCV, and scikit-image.
- Experience with microscopy, histopathology, and radiology image datasets.
- Knowledge of image preprocessing, segmentation, and 3D/volumetric data handling.
- Familiarity with data annotation, weak supervision, or multi-modal learning is a plus.
- Excellent communication and problem-solving skills.
Educational Qualifications
- Prior experience integrating image data with omics, clinical, or molecular datasets.
- Experience deploying ML models or using MLOps tools (e.g., MLFlow, ClearML).
- Publications or open-source contributions in biomedical imaging or computational biology.