Senior Scientist, Computational Protein Design
Job Description
At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.
Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so.
Does this inspire you and feel like a fit? Then we would love to have you join us!
The Role
Genmab is seeking a Senior Data Scientist with a strong technical and machine learning background in combination with molecular modeling experience to join the Discovery Data Science department in Utrecht or Copenhagen.
In this highly collaborative, hands-on role, you will become part of a multidisciplinary, international team of experienced data scientists and senior data science associates with expertise spanning bioinformatics, immunology, antibody development, and therapeutic discovery. Together, you will apply machine learning models to molecular and experimental data to accelerate the discovery of innovative antibody therapeutics for cancer and immune diseases.
As a Senior Data Scientist, you will develop and apply machine learning methods across areas such as protein structure modelling, generative modelling, antibody property prediction, that support therapeutic discovery. Working with diverse antibody-related datasets, including protein sequences, protein structures, and experimental screening data, you will translate complex molecular data into predictive models and actionable insights that directly support the development of innovative medicines. In addition, you will contribute to reusable scientific software and scalable machine learning workflows. As part of a fully integrated biotechnology company, you will contribute throughout the drug discovery journey, from early research through translation towards the clinic.
Responsibilities
Collaborate closely with data scientists, computational scientists, data engineers, and laboratory scientists to curate, process, model, and analyse molecular and experimental data.
Evaluate, adapt, and improve machine learning models that accelerate and optimise therapeutic discovery.
Identify opportunities to apply machine learning, molecular modelling, and advanced computational methods to improve discovery workflows.
Lead or contribute to machine learning projects, providing technical expertise and scientific input throughout project discussions.
Translate complex technical concepts into clear insights through effective visualisations, reports, and presentations.
Work independently while collaborating across Discovery, Engineering, and other cross-functional teams.
Develop robust, reproducible, and maintainable code following established software development best practices.
Requirements
To succeed in this role, you bring a combination of scientific curiosity, technical expertise, and collaborative skills. You also have:
A PhD in Machine Learning, Data Science, Computational Biology, Bioinformatics, Computer Science, Applied Mathematics, Biophysics, Engineering, or another relevant technical discipline.
2-4 years of postdoctoral and/or industry experience in machine learning, computational biology, molecular modelling, or a related data science role.
A solid understanding of modern machine learning principles, including data preprocessing, model development, validation, evaluation, MLOps, statistics, and model interpretation.
Strong programming skills in Python, command-line environments, and version control systems such as Git, with experience writing robust, structured, and reproducible code following software engineering best practices.
At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.
Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so.
Does this inspire you and feel like a fit? Then we would love to have you join us!
The Role
Genmab is seeking a Senior Data Scientist with a strong technical and machine learning background in combination with molecular modeling experience to join the Discovery Data Science department in Utrecht or Copenhagen.
In this highly collaborative, hands-on role, you will become part of a multidisciplinary, international team of experienced data scientists and senior data science associates with expertise spanning bioinformatics, immunology, antibody development, and therapeutic discovery. Together, you will apply machine learning models to molecular and experimental data to accelerate the discovery of innovative antibody therapeutics for cancer and immune diseases.
As a Senior Data Scientist, you will develop and apply machine learning methods across areas such as protein structure modelling, generative modelling, antibody property prediction, that support therapeutic discovery. Working with diverse antibody-related datasets, including protein sequences, protein structures, and experimental screening data, you will translate complex molecular data into predictive models and actionable insights that directly support the development of innovative medicines. In addition, you will contribute to reusable scientific software and scalable machine learning workflows. As part of a fully integrated biotechnology company, you will contribute throughout the drug discovery journey, from early research through translation towards the clinic.
Responsibilities
Collaborate closely with data scientists, computational scientists, data engineers, and laboratory scientists to curate, process, model, and analyse molecular and experimental data.
Evaluate, adapt, and improve machine learning models that accelerate and optimise therapeutic discovery.
Identify opportunities to apply machine learning, molecular modelling, and advanced computational methods to improve discovery workflows.
Lead or contribute to machine learning projects, providing technical expertise and scientific input throughout project discussions.
Translate complex technical concepts into clear insights through effective visualisations, reports, and presentations.
Work independently while collaborating across Discovery, Engineering, and other cross-functional teams.
Develop robust, reproducible, and maintainable code following established software development best practices.
Requirements
To succeed in this role, you bring a combination of scientific curiosity, technical expertise, and collaborative skills. You also have:
A PhD in Machine Learning, Data Science, Computational Biology, Bioinformatics, Computer Science, Applied Mathematics, Biophysics, Engineering, or another relevant technical discipline.
2-4 years of postdoctoral and/or industry experience in machine learning, computational biology, molecular modelling, or a related data science role.
A solid understanding of modern machine learning principles, including data preprocessing, model development, validation, evaluation, MLOps, statistics, and model interpretation.
Strong programming skills in Python, command-line environments, and version control systems such as Git, with experience writing robust, structured, and reproducible code following software engineering best practices.
The ability to translate complex technical concepts into practical analyses and modelling approaches, and communicate findings clearly to colleagues with diverse scientific backgrounds.
Experience applying machine learning to molecular or biological data. Experience with proteins, protein sequences, protein structures, antibody-related data, or therapeutic protein discovery is considered an advantage.
Experience developing, fine-tuning, or improving machine learning models. Exposure to advanced approaches such as protein language models, graph neural networks, geometric deep learning, generative modelling, inverse folding, or structure-based prediction is highly valued.
Experience working with large-scale computational workloads on HPC, cloud, or similar computing environments, and building reusable scientific software or machine learning pipelines, is an advantage.
Experience working in drug discovery, biotechnology, pharmaceutical research, or another applied research environment is beneficial.
A proactive, goal-oriented mindset and the ability to work effectively in multidisciplinary, collaborative research teams.
Excellent written and spoken English.
The proposed gross annual/hourly base salary range for this position, in the primary location, based on a full time schedule is:
DKK658.512,00---987.768,00The final salary offer will depend on several factors, including your skills, qualifications, and experience.
In addition to base salary, this position is eligible for additional forms of compensation, such as discretionary bonuses and long-term incentives.
When you join Genmab, you become a part of a culture that supports your physical, financial, social, and emotional well-being. Our benefits include, but are not limited to:
- Pension
- Health insurance and wellness benefits
- Paid time off
- Employee support programs
Further details on eligibility for compensation and benefits based on the role will be provided during the recruitment process.
About Genmab
Genmab is an international biotechnology company with a core purpose to improve the lives of patients through innovative and differentiated antibody therapeutics. For 25 years, its hard-working, innovative and collaborative team has invented next-generation antibody technology platforms and harnessed translational, quantitative and data sciences, resulting in a proprietary pipeline including bispecific T-cell engagers, antibody-drug conjugates, next-generation immune checkpoint modulators and effector function-enhanced antibodies. By 2030, Genmab’s vision is to transform the lives of people with cancer and other serious diseases with Knock-Your-Socks-Off (KYSO®) antibody medicines.
Established in 1999, Genmab is headquartered in Copenhagen, Denmark with international presence across North America, Europe and Asia Pacific. For more information, please visit Genmab.com and follow us onLinkedInandX.
Genmab is committed to protecting your personal data and privacy. Please see our privacy policy for handling your data in connection with your application on our websiteJob Applicant Privacy Notice (genmab.com).
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