Where Artificial Intelligence Meets Cutting-Edge Antibody Research
Are you passionate for making a meaningful impact on the development of life-saving therapies Join our interdisciplinary team at the forefront of antibody discovery and engineering.
Your Responsibilities:
- You will be responsible for developing and implementing advanced machine learning algorithms that accelerate the discovery and engineering of antibodies. These algorithms will play a key role in improving the efficiency and precision of our research processes.
- In this role you will work closely with cross-functional teams including biologists bioinformaticians and software engineers to ensure that machine learning solutions are seamlessly integrated into existing research workflows. Your ability to collaborate across disciplines will be essential to the success of our projects.
- You will analyze large-scale biological datasets to identify meaningful patterns and generate insights that directly inform antibody design and optimization. Your work will contribute to the development of innovative therapies with real-world impact.
- To stay at the forefront of your field you will continuously monitor and evaluate the latest advancements in machine learning and computational biology. You will apply this knowledge to refine existing methodologies and introduce new technologies that enhance our research capabilities.
- Finally you will communicate your findings and project progress clearly and effectively through presentations technical reports and scientific publications. Your ability to translate complex data into actionable insights will be key to engaging stakeholders and driving innovation.
Qualifications :
- You hold a Masters degree with several years of relevant experience or a PhD in Computer Science Bioinformatics Computational Biology or a closely related discipline.
- Through your academic or professional experience you have gained initial expertise in applying machine learning techniques to biological or biomedical dataideally in the context of antibody or protein research.
- Working in interdisciplinary teams is something you enjoy and you approach new digital challenges with curiosity and openness. You are committed to continuous improvement and demonstrate a structured independent and detail-oriented working style.
- Your strong communication skills enable you to convey complex ideas clearly and you bring a high level of quality awareness and personal responsibility to your work.
- In addition you are proficient in using MS Office and have an excellent command of English both spoken and written. German language skills are an advantage but not essential.
Additional Information :
What we offer
- A modern workplace in Bergisch Gladbach with flexible working hours that allow you to organise your time individually and the option of working from home for two days.
- Diversity: International teams and cross-border intercultural communication
- Room for creativity: Its the most clever solution that we always strive for
- We offer a wide range of corporate benefits and health provision
- Miltenyi University: A clever mind never stops learning take advantage of our inhouse Training Academy
Diversity is the bedrock of our creativity
Our mission: To innovate treatments and technologies and tackle the worlds most serious health challenges. And thats why we connect the dots across various disciplines linking different perspectives skills and abilities.
You and your talent are welcome here in our inclusive and collaborative environment. So come as you are. Regardless of gender sexual identity age ethnicity religion or disability.
We are looking forward to your application
If you have the skills and qualifications for this position please use the link to send us your details. Please give us some idea of when you can start and the kind of salary you are looking for.
Remote Work :
No
Employment Type :
Full-time
Where Artificial Intelligence Meets Cutting-Edge Antibody Research Are you passionate for making a meaningful impact on the development of life-saving therapies Join our interdisciplinary team at the forefront of antibody discovery and engineering.Your Responsibilities:You will be responsible for de...
Where Artificial Intelligence Meets Cutting-Edge Antibody Research
Are you passionate for making a meaningful impact on the development of life-saving therapies Join our interdisciplinary team at the forefront of antibody discovery and engineering.
Your Responsibilities:
- You will be responsible for developing and implementing advanced machine learning algorithms that accelerate the discovery and engineering of antibodies. These algorithms will play a key role in improving the efficiency and precision of our research processes.
- In this role you will work closely with cross-functional teams including biologists bioinformaticians and software engineers to ensure that machine learning solutions are seamlessly integrated into existing research workflows. Your ability to collaborate across disciplines will be essential to the success of our projects.
- You will analyze large-scale biological datasets to identify meaningful patterns and generate insights that directly inform antibody design and optimization. Your work will contribute to the development of innovative therapies with real-world impact.
- To stay at the forefront of your field you will continuously monitor and evaluate the latest advancements in machine learning and computational biology. You will apply this knowledge to refine existing methodologies and introduce new technologies that enhance our research capabilities.
- Finally you will communicate your findings and project progress clearly and effectively through presentations technical reports and scientific publications. Your ability to translate complex data into actionable insights will be key to engaging stakeholders and driving innovation.
Qualifications :
- You hold a Masters degree with several years of relevant experience or a PhD in Computer Science Bioinformatics Computational Biology or a closely related discipline.
- Through your academic or professional experience you have gained initial expertise in applying machine learning techniques to biological or biomedical dataideally in the context of antibody or protein research.
- Working in interdisciplinary teams is something you enjoy and you approach new digital challenges with curiosity and openness. You are committed to continuous improvement and demonstrate a structured independent and detail-oriented working style.
- Your strong communication skills enable you to convey complex ideas clearly and you bring a high level of quality awareness and personal responsibility to your work.
- In addition you are proficient in using MS Office and have an excellent command of English both spoken and written. German language skills are an advantage but not essential.
Additional Information :
What we offer
- A modern workplace in Bergisch Gladbach with flexible working hours that allow you to organise your time individually and the option of working from home for two days.
- Diversity: International teams and cross-border intercultural communication
- Room for creativity: Its the most clever solution that we always strive for
- We offer a wide range of corporate benefits and health provision
- Miltenyi University: A clever mind never stops learning take advantage of our inhouse Training Academy
Diversity is the bedrock of our creativity
Our mission: To innovate treatments and technologies and tackle the worlds most serious health challenges. And thats why we connect the dots across various disciplines linking different perspectives skills and abilities.
You and your talent are welcome here in our inclusive and collaborative environment. So come as you are. Regardless of gender sexual identity age ethnicity religion or disability.
We are looking forward to your application
If you have the skills and qualifications for this position please use the link to send us your details. Please give us some idea of when you can start and the kind of salary you are looking for.
Remote Work :
No
Employment Type :
Full-time
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