Our Research Scientists are our Inventors. We identify and target steps in disease mechanisms or pathways that could be inhibited or enhanced. Our goal is to isolate a compound that is effective against a disease target. Using innovative thinking, state-of-the-art facilities and robust scientific methodology we collaborate to discover the next medical breakthrough.
Become part of a highly cutting edge and innovative Quantitative Biosciences department. Using robust scientific methodology, novel translational models, state-of-the-art instruments and automated equipment, we collaborate to discover the next medical breakthrough. We have added new capability enhancements that allow higher-resolution interrogation of novel biology and the molecular mechanism of action of molecules that help advance the best drug candidates in the clinic.
How to handle and efficiently analyze data with increasing complexity is quickly becoming the next bottleneck. We are therefore seeking an innovative computational scientist to join our company’s Research Laboratory in Boston to help us close this gap who can:
- Develop graphic user-interfaces and optimize pipelines and novel computational approaches to process and analyze highly multidimensional data as those generated from CyTOF, IMC, mIHC, DRUGseq, and high-content image-based profiling experiments e.g. cell painting.
- Become part of a creative and flexible team; collaborate and work closely with bench scientists. Support efforts on the experimental design, analysis, and interpretation of experiments.
- Collaborate with Oncology, Metabolic Disease, Neuroscience and Infectious Disease discovery teams to develop biological hypotheses for computational interrogation
Basic requirements:
- Proficiency in making graphic user interfaces (GUI) for analytics using R Shiny, AngularJS, React.js, etc.
- Experience in optimizing machine learning model performance using low-level languages, such as C++, Java, etc.
- Master’s level understanding of statistics and machine learning techniques such as dimensionality reduction, classification, feature selection, causal inference, regression, supervised/unsupervised learning.
- Proficiency in at least one programming language, such as R or Python
- Bachelor’s level understanding of biology and chemistry
Excellent attention to detail and strong communication (oral and written) skills
Preferred Experience and Skills
- Experience with the computational analysis and interpretation of highly multiplexed datasets
- Experience in high-performance computing hosted in a Unix/Linux OS environment
- Proficiency in at least one deep learning framework, such as TensorFlow, PyTorch, Keras, etc.
- Experience with cytometry (i.e. FACS, CyTOF) and/or histology techniques is a plus
- Highly self-motivated and capable of prioritizing deliverables among multiple simultaneous projects
- Experience in building strong relationships within highly collaborative, multidisciplinary teams
Qualifications/Education
- Bachelor or Master of Science Computational Biology, Bioinformatics, Immunology, Molecular Biology or related field
- 2+ years of working experience in computational biology, bioinformatics and machine learning in a pharma, biotech or academic setting.