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Master Thesis(m/w/x)
Full-time/Part-timeInternshipWith Homeoffice
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BABayer
Master Thesis - Microsolvation in biological systems(m/w/x)
Leverkusen
Full-timeWith Home Office
Nejo AI Summary
Developing workflows for protein-ligand microsolvation using FEBISS at a global health and agriculture company. Computational chemistry and Python programming experience required. Hybrid work option.
Requirements
- Master student in natural science (chemistry, chemical engineering, physics, or comparable)
- Knowledge of computational chemistry and modeling
- First acquaintance with statistical thermodynamics of solvation is an advantage
- Experience in programming language (e.g. Python)
- Familiarity with computational chemistry tools (visualization, quantum mechanics, molecular dynamics) is ideal
- Strong foundation in (bio)chemistry
- Flexibility and structured, independent work manner
- Enjoyment of analyzing complex interrelationships and interdisciplinary questions
- Exposure to git and Linux
Tasks
- Develop workflows for placing water molecules in protein ligand systems
- Establish and evaluate the FEBISS method on relevant research cases
- Build a network of contacts in the R&D community at Bayer
- Prepare publications, presentations, and documentation of your work
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Pymol
- Chimera
- Orca
- Amber
- Gromacs
- git
- Linux
Benefits
Flexible Working
- Hybrid work option
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bayer and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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BABayer
Master Thesis - Microsolvation in biological systems(m/w/x)
Leverkusen
Full-timeWith Home Office
Nejo AI Summary
Developing workflows for protein-ligand microsolvation using FEBISS at a global health and agriculture company. Computational chemistry and Python programming experience required. Hybrid work option.
Requirements
- Master student in natural science (chemistry, chemical engineering, physics, or comparable)
- Knowledge of computational chemistry and modeling
- First acquaintance with statistical thermodynamics of solvation is an advantage
- Experience in programming language (e.g. Python)
- Familiarity with computational chemistry tools (visualization, quantum mechanics, molecular dynamics) is ideal
- Strong foundation in (bio)chemistry
- Flexibility and structured, independent work manner
- Enjoyment of analyzing complex interrelationships and interdisciplinary questions
- Exposure to git and Linux
Tasks
- Develop workflows for placing water molecules in protein ligand systems
- Establish and evaluate the FEBISS method on relevant research cases
- Build a network of contacts in the R&D community at Bayer
- Prepare publications, presentations, and documentation of your work
Education
- Currently in higher education
Languages
- English – Business Fluent
Tools & Technologies
- Python
- Pymol
- Chimera
- Orca
- Amber
- Gromacs
- git
- Linux
Benefits
Flexible Working
- Hybrid work option
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Bayer and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
Bayer
Industry
Pharmaceuticals
Description
Das Unternehmen ist entschlossen, die größten Herausforderungen unseres Planeten zu überwinden und zu einer Welt beizutragen, in der genug Nahrung und ausreichende medizinische Versorgung für alle Menschen erreichbar sind.
Not a perfect match?
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