Postdoctoral Fellow: Computational Immunologist / Data Scientist
- Harvard Medical School / BIDMC
- Location: Boston, MA
- Job Number: 7086756
- Posting Date: Oct 7, 2021
- Application Deadline: Open Until Filled
Job DescriptionThe Arnaout Laboratory for Immunomics uses experiments, mathematics, and machines to decipher the human immunome. We are looking for a postdoc-level computational/systems biologist as part of immunome sequencing and analysis projects.
1. Devise, test, and implement computational algorithms for high-throughput data
2. Contribute to the generation of standard protocols and intellectual property
1. PhD degree in physics, mathematics, computational/systems biology, machine learning, artificial intelligence, immunology, bioinformatics, or related field, or equivalent practical experience
2. Hands-on experience designing and implementing computer algorithms, including supervised and unsupervised machine learning methods like Regression analysis, SVM, deep learning (autoencoders, transformers, geometric deep learning, dynamical systems, model decomposition), etc.
3. Hands-on expertise with statistical descriptions of complex systems (e.g. energy, entropy, moments, etc. and see under 2 above) and their theoretical underpinnings
4. Fluency in Unix/Linux environments, Python and ideally other standard bioinformatics tools (e.g. R, Perl, C, bash/csh/zsh, CUDA, OpenGL), ideally including hands-on experience with parallel processing.
5. Demonstrated expertise in computational analysis of large data sets, ideally biological sequence-based data sets, and 3D protein structures
6. Excellent creativity, decision-making, troubleshooting, and English-language communication skills
7. Comfort with and excitement about working in a startup-type atmosphere
1. Prior experience with implementing deep learning methods
2. Prior experience with high-performance computing clusters (SLURM, LSF or PBS schedulers), and AWS
3. Expertise with using Python libraries like Numpy, Scipy, Pandas, Matplotlib, Seaborn, and Tensorflow
4. Prior experience with/training in structural biology, immunology, cancer, and/or infectious disease
5. Experience with web applications/portals (e.g. Shiny Server or Python analogs)
As soon as possible