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Requirements

Job Overview

The Joshi Lab (PI: Dr Priyanka Joshi) is seeking a highly motivated Masters-level Research Associate to join our interdisciplinary team at the intersection of artificial intelligence and protein engineering. This unique position combines cutting-edge computational modeling with hands-on laboratory experimentation to design and validate novel proteins using state-of-the-art protein language models.

Key Responsibilities

Computational Modeling & AI Development

+ Train and fine-tune ESM (Evolutionary Scale Modeling) protein language models on curated datasets to generate novel protein sequences

+ Develop and optimize machine learning pipelines for protein design, including data preprocessing, model training, and validation protocols

+ Analyze protein structure-function relationships using computational tools and databases

+ Implement and maintain bioinformatics workflows for sequence analysis and protein characterization

+ Collaborate on algorithm development to improve protein generation accuracy and diversity

Laboratory Experimentation

+ Express, purify, and characterize computationally designed proteins using standard molecular biology techniques

+ Perform protein purification protocols including chromatography, electrophoresis, and spectroscopic analysis

+ Conduct functional assays to validate AI-generated protein designs and assess their biochemical properties

+ Maintain detailed laboratory records and ensure compliance with safety protocols

+ Troubleshoot experimental procedures and optimize protocols for improved protein yield and purity

Research Integration & Analysis

+ Bridge computational predictions with experimental validation through iterative design-build-test cycles

+ Analyze experimental results to inform and improve machine learning model performance

+ Prepare comprehensive reports documenting both computational and experimental findings

+ Present research results at team meetings and contribute to scientific publications

+ Collaborate with cross-functional teams including computational biologists, biochemists, and software engineers

Work Interactions

The Research Associate will work directly with the PI and collaborate with the lab members and any external collaborators.

Requirements and Qualifications

Education & Experience

+ Master's degree in Computational Biology, Bioinformatics, Machine Learning, Biochemistry, or related field

+ Minimum 1-2 years of experience in both computational modeling and laboratory research

Technical Skills - Computational

+ Proficiency in Python, with experience in machine learning frameworks (PyTorch, TensorFlow, or JAX)

+ Hands-on experience with protein language models, particularly ESM or similar transformer-based architectures

+ Knowledge of bioinformatics tools and databases (UniProt, PDB, BLAST, structural analysis software)

+ Experience with high-performance computing clusters and cloud computing platforms

+ Familiarity with version control systems (Git) and collaborative development practices

Technical Skills - Laboratory

+ Demonstrated expertise in protein expression, purification, and characterization techniques

+ Proficiency in molecular cloning, bacterial/yeast expression systems, and protein chemistry

+ Experience with chromatographic methods (FPLC, HPLC) and analytical techniques (SDS-PAGE, Western blot, mass spectrometry)

+ Knowledge of protein folding, stability analysis, and functional assays

+ Understanding of laboratory safety protocols and quality control procedures

Core Competencies

+ Strong analytical and problem-solving skills with attention to detail

+ Ability to work independently while contributing effectively to team projects

+ Excellent written and verbal communication skills

+ Experience with data visualization and statistical analysis

+ Project management skills and ability to meet deadlines

Preferred Qualifications

+ Experience with protein design software (Rosetta, ChimeraX, PyMOL)

+ Knowledge of structural biology techniques (X-ray crystallography, cryo-EM, NMR)

+ Familiarity with directed evolution and high-throughput screening methods

+ Experience with cloud platforms (AWS, Google Cloud) for computational biology workflows

+ Publication record in peer-reviewed journals

+ Experience with collaborative research environments and interdisciplinary projects

Work Mode Designation

This position has been designated as on campus. Please note that work mode designations are regularly reviewed in order to meet the evolving needs of the University. Such review may necessitate a change to a position’s mode of work designation. Complete details about Georgetown University’s mode of work designations for staff positions can be found on the Department of Human Resources website: https://hr.georgetown.edu/mode-of-work-designation.

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Need some assistance with the application process? Please call 202-687-2500. For more information about the suite of benefits, professional development and community involvement opportunities that make up Georgetown's commitment to its employees, please visit the Georgetown Works website (https://georgetownworks.georgetown.edu/) .

EEO Statement:

GU is an Equal Opportunity Employer (https://policymanual.hr.georgetown.edu/200-hiring-and-employment/201-equal-employment-opportunity-affirmative-action/) . All qualified applicants are encouraged to apply, and will receive consideration for employment without regard to age, citizenship, color, disability, family responsibilities, gender identity and expression, genetic information, marital status, matriculation, national origin, race, religion, personal appearance, political affiliation, sex, sexual orientation, veteran status, or any other characteristic protected by law (https://georgetown.box.com/s/jkc3kxwrf56e1n2km0jh1vj09fvanw70) .

Benefits:

Georgetown University offers a comprehensive and competitive benefit package that includes medical, dental, vision, disability and life insurance, retirement savings, tuition assistance, work-life balance benefits, employee discounts and an array of voluntary insurance options. You can learn more about benefits and eligibility on the Department of Human Resources website (https://benefits.georgetown.edu/staff/enrolling/) .