Machine Learning Research Scientist
2 days ago
CellVoyant is a pioneering biotech company that harnesses the power of AI to predict stem cell differentiation using live cell microscopy and artificial intelligence. By optimising human tissue manufacturing, we aim to unlock new research and therapeutic applications, making a lasting positive impact on society.
About UsWe spun out from the Carazo Salas lab at the University of Bristol in 2022 and are backed by esteemed venture capital firms who have invested in renowned AI companies like DeepMind, Exscientia, Recursion, Wayve, and Abcam.
Job DescriptionWe are seeking an exceptional Machine Learning scientist with expertise in ML and computer vision, proficient in programming languages like Python, cloud infrastructure (e.g., Google Cloud), and experience with relevant software (e.g., Github, Docker). Your primary responsibilities will include advancing the development of our AI models through contributions to research, methodology development, data enhancement, and collection.
Main Responsibilities- Pioneering Research Advancements: Identify and leverage state-of-the-art research papers and cutting-edge methodologies in machine learning to drive innovation in our AI models enabling predictive modelling, detection, classification, and pattern recognition of stem cell populations.
- Data Enrichment: Identify and source open-source multi-modal data sets (e.g., genomics and microscopy imaging) to enhance the robustness of our AI models. Collaborate closely with computational biologists to ensure data relevance and quality.
- Data Strategy and Proof of Concept: Strategically identify essential data requirements and develop data collection approaches to validate proof of concept for our AI models, particularly in the context of microscopy data analysis and genomics-related hypotheses.
- Cross-Functional Collaboration: Collaborate with cross-functional teams, including computational biologists, biologists, data scientists, and software engineers, to drive multidisciplinary research projects. Foster strong communication channels to effectively integrate computer vision techniques into genomics research endeavors.
A Ph.D. degree in a technical subject (e.g., machine learning, AI, computer science, mathematics, physics, statistics). Strong track record of research publications in top-tier AI conferences such as NeurIPS, AAAI, ICLR, ICML, CVPR, ECCV, IJCV. Proficiency in programming languages like Python and cloud infrastructure (e.g., Google Cloud). Experience with relevant software (e.g., Github, Docker) and knowledge of ML/scientific libraries such as TensorFlow, PyTorch, NumPy, and Pandas.
Excellent analytical, problem-solving, and critical-thinking abilities. A collaborative mindset and ability to work closely with computational biologists to identify hypotheses and validate proof of concept are essential for success in this role.
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