The AI Job Search Engine
PostDoc in Computational and Experimental Protein Design(m/w/x)
Developing computational methods for antibody engineering and drug discovery, integrating ML with Molecular Dynamics in a lab-in-the-loop setup. PhD in computational structural biology or related field, with deep ML understanding for protein prediction, required. Direct contribution to breakthrough drug discovery.
Requirements
- Solid understanding of protein biophysics
- Hands-on experience with core laboratory techniques for creating protein variants, such as protein expression and purification, or eagerness to learn
- PhD in a relevant field, such as Computational Structural Biology, Bioinformatics, Biophysics, Biochemistry, or a related field with a strong computational focus
- Deep understanding of machine learning approaches for protein structure and property prediction, and generative models
- Familiarity with structural modeling and design platforms for biomolecules and protein-protein interactions (e.g. MOE, Schrödinger, Rosetta, modeling and docking algorithms)
- Fluency in English and strong oral and written communication skills
- Solid understanding of antibody structure and/or familiarity with immune repertoire sequencing datasets
- Hands-on experience of in vitro testing methods for antibody characterization, such as Surface Plasmon Resonance (SPR)
- Engagement in scientific research continuously since PhD and readiness to start an RPF postdoctoral activity no later than 4 years after completing PhD
Tasks
- Develop and validate novel computational methods for antibody engineering
- Integrate Machine Learning with Molecular Dynamics workflows
- Implement a lab-in-the-loop approach for computational modeling and experimental validation
- Create a predictor for antibody affinity maturation and developability
- Contribute to drug discovery efforts for breakthrough medicines
- Attend and present at scientific meetings
- Interact with the scientific community and publish experimental advances
- Collaborate with host teams and stakeholders on protein design algorithms
Work Experience
- approx. 4 - 6 years
Education
- Doctoral / PhD
Languages
- English – Business Fluent
Tools & Technologies
- MOE
- Schrödinger
- Rosetta
- Surface Plasmon Resonance (SPR)
Not a perfect match?
- Roche Diagnostics GmbHFull-timeOn-siteManagementPenzberg
- Roche Diagnostics GmbH
Principal Information Scientist / Computational Chemist(m/w/x)
Full-timeOn-siteExperiencedPenzberg - Roche Diagnostics GmbH
Science and Matrix Lead in the environment of Advanced Cell-based Assays for Neuroscience Drug Discovery(m/w/x)
Full-timeOn-siteManagementPenzberg - Roche Diagnostics GmbH
Senior Data Engineer(m/w/x)
Full-timeOn-siteSeniorPenzberg - Roche Diagnostics GmbH
Internship in Automation Solutions for Antibody Development(m/w/x)
Full-timeInternshipOn-sitePenzbergfrom 2,268 / month
PostDoc in Computational and Experimental Protein Design(m/w/x)
Developing computational methods for antibody engineering and drug discovery, integrating ML with Molecular Dynamics in a lab-in-the-loop setup. PhD in computational structural biology or related field, with deep ML understanding for protein prediction, required. Direct contribution to breakthrough drug discovery.
Requirements
- Solid understanding of protein biophysics
- Hands-on experience with core laboratory techniques for creating protein variants, such as protein expression and purification, or eagerness to learn
- PhD in a relevant field, such as Computational Structural Biology, Bioinformatics, Biophysics, Biochemistry, or a related field with a strong computational focus
- Deep understanding of machine learning approaches for protein structure and property prediction, and generative models
- Familiarity with structural modeling and design platforms for biomolecules and protein-protein interactions (e.g. MOE, Schrödinger, Rosetta, modeling and docking algorithms)
- Fluency in English and strong oral and written communication skills
- Solid understanding of antibody structure and/or familiarity with immune repertoire sequencing datasets
- Hands-on experience of in vitro testing methods for antibody characterization, such as Surface Plasmon Resonance (SPR)
- Engagement in scientific research continuously since PhD and readiness to start an RPF postdoctoral activity no later than 4 years after completing PhD
Tasks
- Develop and validate novel computational methods for antibody engineering
- Integrate Machine Learning with Molecular Dynamics workflows
- Implement a lab-in-the-loop approach for computational modeling and experimental validation
- Create a predictor for antibody affinity maturation and developability
- Contribute to drug discovery efforts for breakthrough medicines
- Attend and present at scientific meetings
- Interact with the scientific community and publish experimental advances
- Collaborate with host teams and stakeholders on protein design algorithms
Work Experience
- approx. 4 - 6 years
Education
- Doctoral / PhD
Languages
- English – Business Fluent
Tools & Technologies
- MOE
- Schrödinger
- Rosetta
- Surface Plasmon Resonance (SPR)
About the Company
Roche Diagnostics GmbH
Industry
Pharmaceuticals
Description
Das Unternehmen setzt sich dafür ein, Krankheiten zu verhindern, zu stoppen und zu heilen, und gewährleistet den Zugang zur Gesundheitsversorgung.
Not a perfect match?
- Roche Diagnostics GmbH
Senior Science and People Lead in Bioconjugation and Protein Engineering(m/w/x)
Full-timeOn-siteManagementPenzberg - Roche Diagnostics GmbH
Principal Information Scientist / Computational Chemist(m/w/x)
Full-timeOn-siteExperiencedPenzberg - Roche Diagnostics GmbH
Science and Matrix Lead in the environment of Advanced Cell-based Assays for Neuroscience Drug Discovery(m/w/x)
Full-timeOn-siteManagementPenzberg - Roche Diagnostics GmbH
Senior Data Engineer(m/w/x)
Full-timeOn-siteSeniorPenzberg - Roche Diagnostics GmbH
Internship in Automation Solutions for Antibody Development(m/w/x)
Full-timeInternshipOn-sitePenzbergfrom 2,268 / month