Description & Requirements
We are looking for a highly motivated individual to join the Karczewski lab in the Medical and Population Genetics Program at the Broad Institute. This person will be responsible for building, benchmarking, and applying deep learning methods to identify and characterize disease mutations. The candidate should have a very strong computational background and flexibility to learn and apply new skills.
The Broad Institute provides a vibrant multidisciplinary research environment with close links to MIT, Harvard, and the Harvard-affiliated hospitals across Boston. As a member of our team, you will be provided the opportunity for your contributions to be utilized and recognized across the vast global network of researchers in the fields of genomics and computational biology.
CHARACTERISTIC DUTIES
- Build tools and methods for large-scale genomic deep learning applications, such as fine-tuning protein language models for various biological applications.
- Develop fusion models for multi-modal learning of biomedical data, with data privacy in mind.
- Implement deep learning models of multi-omic data to interpret association studies.
- Work closely with analyst colleagues to understand and benchmark existing computational methods.
- Create pipelines using existing analysis tools to process data in an automated and efficient fashion.
- Create reports from data analysis and communicate these to computational staff.
QUALIFICATIONS
- M.S. required in mathematics, computer science, statistics, bioinformatics or other data sciences. Biology graduates with considerable computational experience will also be considered.
- A minimum of 3+ years of related experience with a BS degree, OR a master’s degree in a related field with 1+ years of related experience.
- Solid understanding of deep learning methods, with experience using at least one of the following frameworks: Pytorch, TensorFlow/Keras, JAX.
- Familiarity with Google Cloud Platform and/or Amazon Web Services, particularly using GPUs, a plus.
- Experience with or interest in analyzing large-scale biological data.
- Demonstrated attention to detail and analytical skills.
- Excellent communication and interpersonal skills.
- Excellent written and oral presentation skills.
- Strong initiative and ability to take ownership of assigned tasks and projects.
- Must be flexible and able to respond to shifting priorities in a dynamic setting.