Postdoctoral Research Fellow- Quantitative Biosciences
The Quantitative Biosciences department is looking for a passionate and talented Postdoctoral Researcher to join the in vivo Quantitative Biosciences team based in West Point, PA. Our company seeks to drive innovation and accelerate pre-clinical research and development by employing data and digital approaches. Towards this goal, the successful candidate will develop a bioinformatics workflow incorporating language and data mining, machine learning, as well as network analysis on existing literature and data to recommend the best in vivo vaccine research strategies. The successful candidate will validate the predictability of their analysis in an experimental pre-clinical mouse model of vaccine efficacy. The extent of bacterial infection protection and immune responses elicited will be characterized in this animal model, providing a unique opportunity to do both in silico and bench work (in vivo and in vitro laboratory research). This is a highly collaborative project working across different functional teams encompassing data science, bioinformatics, immunology, infectious disease, and vaccinology.
our company’s Research Laboratories’ Postdoctoral Research Fellow Program aims to be a best-in-industry program for industrial postdoctoral researchers. We provide an academic focus in a commercial environment with the goal to publish. Postdoctoral researchers will have access to the resources, reach, and expertise of a large pharmaceutical company to conduct breakthrough and innovative research.
- Build novel natural language processing (NLP) and bioinformatics workflow, including network analysis, to guide and accelerate in vivo vaccinology research.
- Evaluate and implement novel enabling technologies and methods as needed.
- Directly test the application of your data science and machine learning products to real-world challenges using pre-clinical animal models of efficacy
- Must be willing to perform in vivo studies and other related wet lab work.
- Remain compliant with all company required trainings and safety regulations.
- Ensure high quality data generation and proper documentation of experimental designs, protocols, and findings.
- Work independently and collaboratively across multi-disciplinary teams
- Drive project direction and publication strategy
- Publish research findings in peer-reviewed journals, present at internal meetings and scientific conferences.
A PhD, with less than 2 years of prior postdoctoral experience, in bioinformatics or a similar discipline with relevant experience on natural language processing (NLP) models, information retrieval, semantic processing, and structured databases, knowledge graph or related techniques. Immunology or Biology background is highly preferred.
Desired experience and skills:
- Fluency in either Python programming, including regular expressions, version control and collaboration with git, standard packages (e.g., pandas, numpy, matplotlib), and at least one machine learning framework (e.g., pytorch, tensorflow, scikit-learn)
- Proficiency with NLP libraries (e.g., Spacy, SemRep), text annotation tools, semantic frameworks (e.g. RDF triplestores, property graphs), linked data query languages (e.g., SPARQL), and/or biomedical ontologies (e.g., UMLS, EFO)
- Experience with knowledge graphs and network analysis
- Experience with Object-Oriented Programming
- Working knowledge of statistical learning, such as supervised, unsupervised, and weakly supervised learning, particularly in NLP and network analysis contexts
- Understanding of Biology and Immunology in the context of vaccinology research, and a strong interest in gaining additional hands-on in vivo and in vitro laboratory (“bench science”) experience to complement in silico work.
- Basic bench science experience working in wet lab.
- Hands on experience with in vitro assays (e.g., ELISAs, bacterial culture)
- Work with animal models
- Excellent communication, teamwork, leadership skills, including skills for scientific communication (authoring scientific articles and presenting)
- Experience with omics datasets and analyses, such as pathway enrichment analysis and inference based on protein-protein interaction networks, a plus.