2025 Molecular Profiling and Drug Delivery Computational Chemistry Intern
AbbVie 98000.00 US Dollar . USD Per annum
2024-11-10 05:39:31
Worcester, Massachusetts, United States
Job type: fulltime
Job industry: Science & Technology
Job description
Company Description
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas immunology, oncology, neuroscience, and eye care and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at . on Twitter , Facebook , Instagram , YouTube and LinkedIn .
Job Description
Molecular Profiling and Drug Delivery Computational Chemistry Internship Overview
Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for AbbVie Interns.
The Molecular Profiling and Drug Delivery (MPDD) function within the Small Molecule CMC organization is accountable for a broad range of deliverables across various stages of drug discovery and development. During lead optimization and through candidate selection, MPDD scientists utilize state of the art automation and computational tools supported by expertise in biopharmaceutics, drug delivery, and solid-state chemistry to collaboratively progress candidates with higher probability of success into development and advise clinical formulation strategy. From candidate selection through clinical proof of concept and product launch, MPDD scientists work in cross-functional teams to identify the commercial solid form of the active pharmaceutical ingredient (API) and establish structure-property-performance correlations to help deliver robust commercial processes and align control strategies across drug substance and product. Computational chemists within AbbVie's MPPD organization work collaboratively with other functions within Development Sciences and Discovery across three focus areas: molecular design, material design, and structural determinants of absorption, towards the vision to model low dose compounds with optimal potency, clearance, permeability, and solubility prior to synthesis and to gain an atomistic level understanding of materials properties and performance.
AbbVie's MPPD organization is seeking a highly motivated, talented, and creative early-career scientist with experience in computational chemistry and atomistic molecular simulations for a Computational Chemistry Intern position. This intern will use molecular modeling (including molecular dynamics and other atomistic methods) to improve understanding of structural determinants of permeability of beyond-rule-of-five (bRo5) and emerging drug modalities. This intern will help investigate and validate improved methods for permeability assessment and determine the extent and conditions of applicability for these capabilities.
Key responsibilities include:
- Conduct molecular dynamics simulations to calculate physicochemical properties such as lipophilicity which are correlated with permeability
- Incorporate more accurate solvent models and enhanced sampling techniques into in-house lipophilicity methods
- Analyze simulation data for correlations and predictive power for permeability and associated ADME properties
Qualifications
MinimumQualifications
- Currently enrolled in university, pursuing a PhDin chemistry, chemical engineering, biological engineering, computational chemistry, or other related field
- Must be enrolled in university for at least one semester following the internship
- Knowledge in one or more areas of computational chemistry, such as molecular dynamics, quantum mechanics, structure-property relationship modeling, and physicochemical property prediction
- Experience using open-source or commercial QM or MD packages, with the ability to build, integrate, and automate computational models from different programs
- Working proficiency of Python
- Expected graduation date between December 2025 July 2026
- Fundamental knowledge of the following areas related to physics-based modeling: statistical mechanics, thermodynamics, quantum mechanics
- Experience with one or more of the following computational methods: enhanced sampling methods, free energy calculations, implicit solvent methods, conformational sampling
- Competitive pay
- Relocation support for eligible students
- Select wellness benefits and paid holiday / sick time
- Opportunity to connect with AbbVie leaders and scientists
- Exposure to AbbVies broad project portfolio and experience the interface between Discovery and CMC Development
At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes ingood faith it will pay for this role at the time of this posting based on the job grade for this position. Individualcompensation paid within this range will depend on many factors including geographic location, and we may ultimatelypay more or less than the posted range. This range may be modified in the future.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion. It is AbbVies policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status.
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