Postdoctoral Fellow I

Project Description

The Kaundal Artificial Intelligence and Advanced Bioinformatics Lab, KAABiL (https://kaabil.net/) at the Center for Integrated BioSystems (CIB), Department of Plants, Soils, & Climate, Utah State University (USU), is inviting applications for a Postdoctoral Research Fellow under the recently awarded grant to investigate the mechanisms of Host-Pathogen interactions on a genome scale.

The project, entitled “Decoding the Poultry-HPAI Interactome: An Integrative Pipeline for Targeted herapeutics Against Highly Pathogenic Avian Influenza” will address the mechanisms of pathogenesis and develop novel therapeutics to address HPAI control in poultry (e.g. comparative analysis of multiple host-pathogen Protein Interaction Networks (PINs) that may allow us to identify conserved mechanisms of pathogen cellular invasion), and (ii) provide bioinformatics solutions / tools to curate and visualize such PINs in a user-friendly way, leading to advance host-targeted antiviral discovery.

Responsibilities

• Develop systems bioinformatics approaches including Machine Learning-based to decipher host-pathogen interaction networks in diverse Avian and HPAI strains.
• Focus on system and data integration, algorithm development and computational modeling of the interactions among pathogen proteins and host proteins using diverse data types or properties.
• Specific responsibilities include:
• Comprehensive computational mapping of avian-HPAI host-pathogen interactions, including proteomic and transcriptomic approaches,
• In silico drug target identification and therapeutic candidate screening, e.g. Structure-based computational screening using molecular docking, high-throughput virtual screening, and molecular dynamics (MD) simulations,
• Implementation of a public database and predictive tool development, an intuitive UI for hypothesis testing and exploratory research.
• In addition, the candidate is also expected to explore the applicability of these tools on relevant host-pathogen interaction systems.

Qualifications

• Minimum Qualifications: Ph.D. degree in Biology, Computer Science, Engineering, Math/Stats, or related life sciences field.
• Programming skills with Python, R, Java, C/C++, or Perl, and efficiency in Linux / UNIX operating systems.
• Independent problem-solving skills.
• Good communication skills, strong team-work spirit, and self-learning abilities.

Preferred Qualifications

• Ph.D. degree in Computational Biology, Genomics, Bioinformatics, Computer Science or highly related field.
• Experience in developing Machine Learning-based models and large-scale data analysis systems.
• Knowledge about PINs, graphical models such as the dynamic Bayesian networks.

Required Documents

• Along with the online application, please attach:
  • Resume/CV to be uploaded at the beginning of your application in the Candidate Profile under “Resume/CV”
  • Statement of your research interests to be uploaded at the beginning of your application in the Candidate Profile under “Documents 1-10”
  • Three professionl references with contact information

Document size

May not exceed 10 MB.