Kinetica has partnered with an innovator of genomics bioinformatics software company dedicated to advancing genomic research and personalized medicine. Our innovative solutions empower scientists and researchers with state-of-the-art tools to analyze and interpret genomics data.
Our client is seeking a talented Machine Learning Engineer to join our dynamic team in Europe. The ideal candidate will have a strong background in machine learning, structural antibody knowledge, and proficiency in coding. As a Machine Learning Engineer, you will play a key role in developing and implementing machine learning algorithms for the analysis of genomics data, particularly focusing on structural antibody applications.
- Collaborate with cross-functional teams to understand and define machine learning requirements for genomics bioinformatics software.
- Design, implement, and optimize machine learning algorithms for the analysis of structural antibody data.
- Develop and maintain robust and scalable code for genomics data processing and analysis.
- Work closely with bioinformaticians and computational biologists to integrate machine-learning models into existing software platforms.
- Stay current with advancements in machine learning, genomics, and structural antibody research to contribute to the continuous improvement of our solutions.
- Collaborate with the software development team to deploy and integrate machine learning models into production environments.
- Master's or Ph.D. in Computer Science, Bioinformatics, Computational Biology, or a related field.
- Proven experience in machine learning with a focus on genomics and bioinformatics.
- Strong understanding of structural antibody data and its applications in genomics research.
- Proficiency in programming languages such as Python, Java, or C++.
- Familiarity with popular machine learning frameworks (e.g., TensorFlow, PyTorch).
- Experience with genomics data analysis tools and software.
- Excellent problem-solving skills and the ability to work collaboratively in a team environment.
- Strong communication skills and the ability to convey complex technical concepts to non-technical stakeholders.
Interested candidates are invited to submit their CVs.