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Head of Data, BI, and AI @ In Technology Group.
Job Title: Machine Learning Engineer (Medical & Drug Discovery)
Location: Oxford (2 days a week onsite)
Salary: Flexible (Up to £80,000 DOE)
This one is for one of my best clients who is at the forefront of innovation in the medical and drug discovery sector. They are genuinely dedicated to leveraging cutting-edge machine learning techniques to accelerate breakthroughs in healthcare. If you’re passionate about using AI to solve complex biological and pharmaceutical challenges, join our team to help shape the future of medicine.
Job Description:
As a Machine Learning Engineer specializing in the medical and drug discovery domain, you’ll design, implement, and optimize AI models that drive innovation in biomedical research. You will work closely with data scientists, bioinformaticians, and domain experts to turn vast datasets into actionable insights.
Key Responsibilities:
- Develop, train, and deploy machine learning models for tasks such as protein structure prediction, drug-target interaction, and biomarker discovery.
- Engineer data pipelines to handle large-scale biomedical datasets, including genomics, clinical trials, and molecular data.
- Implement and optimize deep learning architectures (e.g., CNNs, RNNs, transformers) for biological sequence analysis and imaging data.
- Apply NLP models to process biomedical literature and clinical data.
- Collaborate with cross-functional teams, including biologists and chemists, to define requirements and ensure model outputs align with scientific goals.
- Monitor model performance and retrain as necessary to improve accuracy and generalization.
- Stay current on advancements in ML, bioinformatics, and drug discovery to continuously enhance our models.
Requirements:
- Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or a related field.
- Strong proficiency in Python and machine learning frameworks like TensorFlow, PyTorch, or scikit-learn.
- Experience with specialized bioinformatics tools and libraries (e.g., Biopython, RDKit, DeepChem).
- Solid understanding of statistical models, deep learning architectures, and data preprocessing techniques.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Knowledge of databases (SQL, NoSQL) and data engineering for large, diverse datasets.
- Excellent problem-solving skills and ability to collaborate with interdisciplinary teams.
- Strong communication skills, with the ability to convey technical results to non-technical audiences.
Preferred Qualifications:
- Experience with generative models (e.g., GANs, VAEs) for molecule generation.
- Knowledge of molecular docking, cheminformatics, or systems biology.
- Exposure to regulatory considerations and data privacy in healthcare AI.
Join and contribute to transforming healthcare through AI-powered discoveries. Your work could be the key to the next breakthrough drug or lifesaving treatment.
Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Analyst, Information Technology, and Research
Industries
Biotechnology Research, Research Services, and Pharmaceutical Manufacturing
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