Machine Learning Scientist
3 weeks ago
About the Role:
We are seeking a talented and motivated Machine Learning Scientist to join our team, contributing to the development of advanced ML solutions for analyzing complex biological datasets. This role offers an exciting opportunity to work at the intersection of machine learning and life sciences, enabling transformative insights from multi-omics and biomedical data.
Key Responsibilities:
- Design, implement, and optimize machine learning algorithms for analyzing biological data, including genomics, transcriptomics, mass spec, and imaging datasets.
- Develop approaches to integrate diverse data types (e.g., multi-omics, clinical, imaging) to derive meaningful biological insights.
- Stay updated with state-of-the-art ML methods and their applications in life sciences to propose innovative solutions.
- Work closely with bioinformaticians, data scientists, and domain experts to ensure seamless integration of ML models into workflows.
- Optimize and deploy ML models on cloud platforms for scalable analysis.
- Collaborate on preprocessing, feature engineering, and quality control of large, noisy biological datasets.
Qualifications:
- Ph.D. or Master’s degree (2-3 years experience) in Machine Learning, Computer Science, Bioinformatics, Computational Biology, or a related field.
- Solid understanding of machine learning algorithms (e.g., supervised, unsupervised, deep learning) and statistical methods.
- Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong problem-solving skills with an aptitude for interpreting complex biological data.
- Excellent communication and interpersonal skills, with the ability to work effectively in a collaborative environment.
- Experience working with cloud technologies (like AWS, GCP, Azure) and scalable computing platforms
Good-to-have:
- Experience with biological datasets (e.g., NGS, proteomics, or imaging) and applying ML to multi-omics data integration.
- Experience working with cloud technologies and scalable computing platforms
- Familiarity with biomedical ontologies, pathway analysis, or systems biology approaches.
- Strong publication record in ML or bioinformatics journals.
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