Inceptive
Foundation and generative models for biomolecules(m/w/x)
Full-timeOn-siteExperienced
Berlin
from USD 135,000 - 240,000 / year
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PFPfizer Pharma GmbH
Postdoctoral Fellow, Machine Learning Research(m/w/x)
Berlin
Full-timeOn-siteExperienced
AI/ML
Nejo AI Summary
Developing and deploying ML methods on protein-ligand datasets, predicting drug-like binders for disease targets, integrating multimodal data. PhD with research experience in ML/DL solutions and expertise in ML for chemistry essential. Researching solutions for serious disease treatment and well-being improvement.
Requirements
- Formal training in Physics, Chemistry, Computational Chemistry, Statistics, or related technical discipline
- PhD and relevant research experience in developing machine/deep learning-based solutions
- Hands-on experience in handling, processing, integrating, and analyzing large heterogeneous data sets
- Proven expertise in developing machine learning for chemistry and molecular representation learning
- Highly creative person with outstanding problem-solving skills
- Strong publication record and demonstrated contributions to the field
- Solid expertise with libraries such as PyTorch, Lightning, RDKit and top-notch programming skills in Python
- Familiarity with GPU computing on-premises and on cloud platforms
- Passion and curiosity for data and proven ability to take ideas from prototype to production
- Strong interpersonal skills and distinct collaborative attitude
Tasks
- Develop and deploy ML methods on protein-ligand datasets
- Predict drug-like binders for disease-relevant targets
- Advance binder prediction using open protein-ligand datasets
- Build and validate learning methods for multimodal data integration
- Research and implement algorithms for protein-ligand interaction modeling
- Collaborate with high-throughput screening labs and data engineering
- Conceive, execute, and evaluate studies and experiments
- Interpret results and present findings to academic and industry scientists
- Publish and present work in reputable journals and conferences
- Engage with the scientific community by open-sourcing models and tools
Work Experience
- approx. 1 - 4 years
Education
- Doctoral / PhD
Languages
- English – Business Fluent
Tools & Technologies
- PyTorch
- Lightning
- RDKit
- Python
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Pfizer Pharma GmbH 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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PFPfizer Pharma GmbH
Postdoctoral Fellow, Machine Learning Research(m/w/x)
Berlin
Full-timeOn-siteExperienced
AI/ML
Nejo AI Summary
Developing and deploying ML methods on protein-ligand datasets, predicting drug-like binders for disease targets, integrating multimodal data. PhD with research experience in ML/DL solutions and expertise in ML for chemistry essential. Researching solutions for serious disease treatment and well-being improvement.
Requirements
- Formal training in Physics, Chemistry, Computational Chemistry, Statistics, or related technical discipline
- PhD and relevant research experience in developing machine/deep learning-based solutions
- Hands-on experience in handling, processing, integrating, and analyzing large heterogeneous data sets
- Proven expertise in developing machine learning for chemistry and molecular representation learning
- Highly creative person with outstanding problem-solving skills
- Strong publication record and demonstrated contributions to the field
- Solid expertise with libraries such as PyTorch, Lightning, RDKit and top-notch programming skills in Python
- Familiarity with GPU computing on-premises and on cloud platforms
- Passion and curiosity for data and proven ability to take ideas from prototype to production
- Strong interpersonal skills and distinct collaborative attitude
Tasks
- Develop and deploy ML methods on protein-ligand datasets
- Predict drug-like binders for disease-relevant targets
- Advance binder prediction using open protein-ligand datasets
- Build and validate learning methods for multimodal data integration
- Research and implement algorithms for protein-ligand interaction modeling
- Collaborate with high-throughput screening labs and data engineering
- Conceive, execute, and evaluate studies and experiments
- Interpret results and present findings to academic and industry scientists
- Publish and present work in reputable journals and conferences
- Engage with the scientific community by open-sourcing models and tools
Work Experience
- approx. 1 - 4 years
Education
- Doctoral / PhD
Languages
- English – Business Fluent
Tools & Technologies
- PyTorch
- Lightning
- RDKit
- Python
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Pfizer Pharma GmbH 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.
About the Company
Pfizer Pharma GmbH
Industry
Pharmaceuticals
Description
Das Unternehmen arbeitet daran, das Wohlbefinden und die Heilungschancen gegen schwerwiegende Erkrankungen zu verbessern.
Not a perfect match?
- Inceptive
Foundation and generative models for biomolecules(m/w/x)
Full-timeOn-siteExperiencedBerlinfrom USD 135,000 - 240,000 / year - Pfizer
Intern Machine Learning Research(m/w/x)
Full-timeInternshipOn-siteBerlin - Pfizer Pharma GmbH
Computational Biologist(m/w/x)
Full-timeOn-siteExperiencedBerlin - Perplexity
Machine Learning Research Engineer - Search(m/w/x)
Full-timeOn-siteExperiencedBerlin - Prior Labs
Research Scientist(m/w/x)
Full-timeOn-siteExperiencedBerlinfrom 120,000 / year