Post Doc Res Assoc (Safavi-Hemami Lab)

Post Doc Res Assoc (Safavi-Hemami Lab)

Job Summary

We are seeking a highly motivated Postdoctoral Researcher with a strong background in computational biology to join the Safavi Lab at the University of Utah. The overall objective of the innovative project it to discover and validate signaling peptides with therapeutic potential from diverse natural sources, including animal venoms. This project is in collaboration with Novo Nordisk, and the candidate will benefit from co-supervision and biannual visits to the Novo Nordisk's Boston location.

Our group
The Safavi group focuses on building on and harnessing the explosion in biological sequence data to identify bioactive peptides from natural sources, including animal venoms, to tackle some of the currently most sought-after questions in endocrinology, molecular evolution, and peptide drug discovery. Our group has a strong interest in developing computational tools for sequence analysis with real world application. The international, mixed computational and experimental group is part of the Medical Campus at the University of Utah, and currently consists of four Postdocs, three PhD students, and one technician, all working within a strong international network.

The University of Utah
The University of Utah, located in the dynamic city of Salt Lake City, is a world-class institution known for its research excellence and collaborative academic environment. Nestled at the foot of the majestic Wasatch Mountains, the university offers a stunning backdrop for both work and recreation. Salt Lake City combines the amenities of a metropolitan area with affordable and accessible lifestyle. Residents enjoy year-round opportunities for outdoor adventures, including hiking, skiing, and mountain biking, with five national parks and numerous scenic destinations just a short drive away. The city boasts a growing arts and culture scene, diverse dining options, and a welcoming community.

Responsibilities
Signaling peptides (i.e., peptide hormones and neuropeptides) play crucial roles in physiological processes, making them highly relevant for therapeutic development. While recent advances in genomics, transcriptomics, and proteomics have identified a wealth of putative signaling peptides encoded by small Open Reading Frames (smORFs), identifying genuine candidates remains challenging. This project will leverage state-of-the-art machine learning and bioinformatics to address key challenges in identifying signaling peptide candidates, predicting their bioactive forms, and pinpointing their target receptors. The role will involve developing and integrating computational tools and data from venom research with existing methodologies for smORF discovery. By combining advanced computational techniques and biological insights, the postdoc will contribute to groundbreaking discoveries in signaling peptide biology, which may lead to novel drug candidates for various diseases and enhance our understanding of peptide diversity and evolution.

The interdisciplinary nature of the project, which combines bioinformatics and data science with downstream molecular biology and pharmacology, will enhance the candidate's expertise across multiple domains. It thereby not only offers a platform to contribute to transformative research but also paves the way for a future career in both adademic and industry.

Minimum Qualifications


Preferences
Essential Skills and Qualifications

• Ph.D. in Computational Biology, Bioinformatics, Peptide Discovery, or a related field.
• Strong programming skills in languages such as Python, and Bash.
• Experience with bioinformatics tools and software for sequence analysis (e.g., BLAST, AlphaFold).
• Familiarity with machine learning techniques for natural language processing and their application to biological data.
• Familiarity with high-throughput DNA/RNA sequencing technologies and data interpretation.
• Good communication skills, both verbal and written, for effective collaboration and dissemination of findings.

Desired Skills

• Experience with data mining techniques and evolutionary biology analyses.
• Knowledge of neuropeptide and or micropeptide biology and evolution.
• Familiarity with proteomics sequencing technologies and data interpretation.
• Ability to work collaboratively in interdisciplinary teams.
• Experience with scientific writing and publication in peer-reviewed journals.
• Familiarity with graphical tools for data visualization.

Special Instructions
To apply, please submit your CV, a cover letter detailing your research experience and interests, and contact information for two references to helena.safavi@utah.edu.

Requisition Number: PRN40454B
Full Time or Part Time? Full Time
Work Schedule Summary:
Department: 01502 - Department of Biochemistry
Location: Campus
Pay Rate Range: 64000 - 71352
Close Date: 2/1/2025
Open Until Filled:

To apply, visit https://utah.peopleadmin.com/postings/174607


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