Machine Learning Research Scientist

4 weeks ago

Bristol, Bristol, United Kingdom CellVoyant Full time
Job Title: Machine Learning Research Scientist

CellVoyant is a biotechnology company that leverages live cell microscopy and artificial intelligence to predict stem cell differentiation. We aim to understand and solve important health issues, making a long-lasting positive impact on society.

We are seeking a highly motivated and skilled Machine Learning scientist proficient in ML and computer vision, with a keen interest in genomics and microscopy data. As a Machine Learning scientist, your role will be pivotal in advancing the development of our AI models, contributing to research, methodology development, data enhancement, and collection.

Key Responsibilities:
  1. 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 modeling, detection, classification, and pattern recognition of stem cell populations.
  2. 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, collaborating closely with computational biologists to ensure data relevance and quality.
  3. 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.
  4. Collaboration and Communication: Collaborate with cross-functional teams, including computational biologists, biologists, data scientists, and software engineers, to drive multidisciplinary research projects, fostering strong communication channels to effectively integrate computer vision techniques into genomics research endeavors.
Qualifications:

A strong track record of research publications in top-tier AI conferences such as NeurIPS, AAAI, ICLR, ICML, CVPR, ECCV, IJCV. Ph.D. Degree in a technical subject (e.g., machine learning, AI, computer science, mathematics, physics, statistics). Proficiency in programming languages like Python, cloud infrastructure (e.g., Google Cloud), and experience with relevant software (e.g., Github, Docker). Knowledge of ML/scientific libraries such as TensorFlow, PyTorch, NumPy, and Pandas. Excellent analytical, problem-solving, and critical-thinking abilities. A collaborative mindset and the ability to work closely with computational biologists to identify hypotheses and validate proof of concept are essential for success in this role.

Experience with Large-Scale System Design.

Expertise in Self-Supervised ML and Generative Models such as Auto-encoders and GANs (Generative Adversarial Networks). Familiarity with Advanced Decision-Making Approaches such as Deep Reinforcement Learning (DRL), Imitation Learning (IL), and learning from demonstrations. Expertise in Multi-Task and Multi-Modal Learning. Proficiency in Sequential Models such as Transformers.

Nice-to-have Skills or Background:
  1. (A big plus) Experience in genomics or bioinformatics research projects in an academic, pharmaceutical, or biotechnology setting.
  2. (A big plus) Experience in microscopy data and their applications.
  3. Proven experience in stem cell research projects in an academic, pharmaceutical, or biotechnology setting.

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