At a Glance
- Tasks: Support antibody discovery and drug development using cutting-edge computational techniques.
- Company: Join a forward-thinking biotech company focused on innovative drug discovery.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and innovation.
- Why this job: Make a real impact in drug discovery while collaborating with top scientists.
- Qualifications: PhD or Master's in relevant field; experience in computational biology preferred.
The predicted salary is between 30000 - 40000 € per year.
Relation is offering an outstanding opportunity for a Data Scientist to support computational drug discovery and drug‑ability efforts focused on antibodies. You will work closely with external deep learning‑driven antibody design platforms to critically evaluate generated candidates, extract insights, and integrate learnings into internal discovery strategies.
DAY TO DAY, YOU WILL:
- Support computational antibody discovery and drug‑ability efforts across research programmes.
- Work with internal and external teams to evaluate and interpret computationally generated antibody candidates.
- Contribute computational and structural biology expertise to multidisciplinary project teams.
- Help extract insights from sequence, structural, and modelling data to inform discovery decisions.
- Collaborate with machine learning and experimental scientists to support ongoing research activities.
- Contribute to the development and refinement of internal computational discovery strategies and workflows.
PROFESSIONALLY, YOU WILL HAVE:
- A PhD in computational biology, structural bioinformatics, computational structural biology, or a related field; or a Master’s degree with equivalent industry experience.
- 0–2 years of experience in biotech, pharma, or a relevant postdoctoral environment.
- Experience with computational approaches for antibody design and development.
- Antibody sequence and repertoire analysis.
- Structural modelling of antibodies and antibody‑antigen complexes.
- Computational protein engineering and affinity optimisation.
- Machine learning and generative modelling for antibody design.
- Developability and biophysical risk assessment.
- Knowledge of Python as a programming language.
- Understanding of the drug discovery process.
Bonus experience:
- Exposure to real‑world drug discovery projects.
- Experience with additional therapeutic modalities such as small molecules, nucleic acids, or degraders.
- Exposure to machine learning.
PERSONALLY, YOU:
- Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.
- Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.
- Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.
- Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.
- Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.
Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age.
Data Scientist, Antibody Design (12-month FTC) employer: Relation
Relation is an exceptional employer that fosters a collaborative and innovative work culture, ideal for Data Scientists passionate about computational drug discovery. With a strong emphasis on professional growth, employees are encouraged to engage in multidisciplinary projects and contribute to cutting-edge research, all while enjoying the benefits of a supportive environment that values diverse perspectives and open communication. Located in a vibrant area, Relation offers unique opportunities to work alongside leading experts in the field, making it a rewarding place for those seeking meaningful and impactful careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist, Antibody Design (12-month FTC)
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend relevant events, and connect with professionals on LinkedIn. We can’t stress enough how valuable personal connections can be in landing that dream job.
✨Tip Number 2
Prepare for interviews by practising common questions and showcasing your expertise in computational biology and antibody design. We recommend doing mock interviews with friends or mentors to boost your confidence.
✨Tip Number 3
Showcase your projects! Whether it’s through a portfolio or GitHub, let your work speak for itself. We love seeing real examples of your skills in action, especially when it comes to machine learning and structural modelling.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we’re always on the lookout for passionate candidates who are ready to make an impact in drug discovery.
We think you need these skills to ace Data Scientist, Antibody Design (12-month FTC)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your relevant experience in computational biology and antibody design. We want to see how your skills align with the role, so don’t be shy about showcasing your expertise!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about this opportunity and how your background makes you a perfect fit for our team. Keep it engaging and personal.
Showcase Your Projects:If you've worked on any relevant projects, especially those involving machine learning or structural modelling, make sure to mention them. We love seeing practical examples of your work that demonstrate your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen on joining our team at StudySmarter!
How to prepare for a job interview at Relation
✨Know Your Stuff
Make sure you brush up on your computational biology and antibody design knowledge. Be ready to discuss your experience with structural modelling and machine learning, as these are key areas for the role. Prepare specific examples of how you've applied these skills in past projects.
✨Show Your Collaborative Spirit
Since this role involves working with various teams, be prepared to talk about your experiences in a matrixed environment. Highlight instances where you've successfully collaborated with others, especially in multidisciplinary settings, and how you contributed to shared goals.
✨Ask Insightful Questions
Prepare thoughtful questions that show your interest in the company's drug discovery process and their approach to antibody design. This not only demonstrates your enthusiasm but also gives you a chance to assess if the company aligns with your career goals.
✨Communicate Clearly
Practice articulating your thoughts clearly and concisely. During the interview, focus on being open and direct in your communication. This will help you build rapport with the interviewers and showcase your ability to handle challenging conversations respectfully.
