Top 108 Quantum algorithm quantum algorithm quantum algorithm quantum physics algorithms Jobs

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Solutions Architect - Financial services (Principal or Director level) - 659
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Senior Scientist I Computational Chemistry

AbbVie -
North Chicago, IL

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Job Details

Full-time
$96,500 - $183,500 a year

Benefits

Paid holidays
Health insurance
Dental insurance
401(k)
Paid time off
Vision insurance

Qualifications

AI models
Software coding
AI platforms (beyond public GPTs)
Computational framework
Computational modeling
Machine intelligence
C
Machine learning libraries
Machine learning frameworks

Full Job Description

Company Description

About AbbVie

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 including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.

Job Description

The Molecular Profiling and Drug Delivery (MPDD) function within the Synthetic Molecule CMC organization is accountable for a broad range of deliverables across various stages of drug discovery and development. During virtual screening/lead generation/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 design and progress candidates with higher probability of success into development and advise clinical drug delivery 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 Sciences across two focus areas: molecular design and profiling and formulation design across modalities. MPDD computational chemists guide the design and progression of compounds and formulations with optimal developability properties towards the overall vision of advancing first-in-class and best-in-class clinical candidates. They focus on developing hierarchical modeling approaches, including physics-based atomistic modeling, encompassing Molecular Dynamics (MD) and Quantum Mechanics (QM), Machine learning (ML)/Artificial Intelligence (AI) and hybrid models based on Physics-ML/AI approaches. They also collaborate seamlessly with medicinal chemists, data scientists, material scientists, and molecular modelers to incorporate these models in project screening funnels and medicinal chemistry design cycle.

AbbVie's MPDD organization is seeking a highly motivated, talented, and creative scientist with experience and expertise in computational chemistry for a Senior Scientist position. This person will make key contributions towards enablement of our modeling vision. Specifically, the person will be working collaboratively with discovery colleagues to develop stage-appropriate computational models using advanced computational techniques to enable design and optimization of drug candidates across modalities. The ideal candidate should possess an advanced degree in computational chemistry with a strong background in the area such as quantum mechanics, atomistic molecular simulations (molecular dynamics) and AI/machine learning.

Responsibilities

In collaboration with Discovery Research and Development Sciences project teams, utilize advanced computational tools towards the design, optimization, and profiling of drug candidates.
Advance computational chemistry capabilities through innovation and implementation of new methodologies and workflows towards capturing key developability properties such as permeability, stability, toxicity, and solubility. Examples include, but are not limited to, utilization of molecular simulations/QM approaches, coupled with AI/ML approaches, to predict dynamic molecular conformations/electronic structure and their impact on Absorption, Distribution, Metabolism, and Excretion, Toxicity (ADMET) properties and Chemistry, Manufacturing and Controls (CMC) properties.
Serve as a lead computational scientist on project teams and drive the development and implementation of appropriate computational models within projects to support various aspects of drug discovery and drug development.
Generate hypotheses for compound property improvement and apply them to new compound design.
Contribute to the development of computational infrastructure by identification of novel tools and techniques.
Act as a strong team player in a cross-functional and collaborative environment.
Demonstrate excellent oral and written communication skills.
Promote design-driven and predict-first culture
Educate and train colleagues on various computational tools and techniques

Qualifications

Bachelors, Masters, or PhD with 8+ (BS), 5+ (MS), and 0-3 (PhD) years of experience in computational chemistry, computer science, biophysics, chemical engineering, or related field
Knowledge in one or more areas of the computational chemistry discipline, such as quantum mechanics/chemistry, molecular reactivity, molecular dynamics, structure-based design, ligand-based design, structure property relationship modeling, physicochemical property prediction
Advanced user of QM or MD software packages. This may include open-source codes (PySCF, Psi4, GROMACS, OpenMM, LAMMPS, etc..) or commercial software (VASP, Schrodinger, OpenEye, MOE, etc).
Ability to build and integrate computational models through combining different workflows while also modifying or improving workflow source codes as needed.
Familiarity with machine learning or neural network packages including but not limited to Scikit-learn, Pytorch,
Well versed in writing codes in Python, R, C/C++ etc.
Nice to have: a candidate with deep understanding of electronic structure methodologies and algorithms, as well as experience with developing quantum circuits/algorithms for quantum computers (i.e. qiskit expertise).

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 in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
This job is eligible to participate in our short-term incentive programs.

Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable toa particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.

US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html

US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:

https://www.abbvie.com/join-us/reasonable-accommodations.html

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