Responsibilities:
- Development of machine learning models for various cancer treatments
- Research and development of new, cutting-edge methods for incorporating raw genomic data into predictive models and drug target discovery
- Data explorative analysis and data mining of genomic data and clinical data.
- Evaluation, visualization, and description of the developed models for scientific publications and patents
- Clear communication of the results to an interdisciplinary team (biologists, bioinformaticians, computer scientists), both in spoken and written form
- Development and maintenance of various libraries and tools used in the process of building machine learning models
Requirements:
- At least 2 years of experience with machine learning and artificial intelligence
- Ability to program in Python (R, Scala is a plus)
- Familiarity with Python data processing stack: Scikit-learn, Pandas, Numpy, PyTorch, Tensorflow
- Outstanding data analysis and visualization skills (Matplotlib, Plotly, Seaborn, Dash, etc.)
- The candidate’s additional advantage would be an experience with big data processing (Spark, pyspark), knowledge of data warehouse systems, Kubernetes, deep learning, Sql, Bash or familiarity with cloud computing (AWS, GCP) or batch processing (e.g. slurm)
- Proactive attitude and excellent communication skills,
- Flexibility and adaptability to changing priorities
- Advanced spoken and written English