Computational/Bioinformatics

Role Overview

Nykode Therapeutics is seeking a Computational/Bioinformatics Scientist to join our In Silico and AI Department. In this newly expanded role, you will apply advanced ML/AI to drive innovation in modular immunotherapies, epitope discovery, and immunoinformatics. Collaborating with expert teams, you will advance research programs targeting cancer and autoimmune diseases. We are looking for a candidate with deep technical expertise and a broad scientific perspective; while computational structural biology experience is a plus, it is not required.  

Key Responsibilities

• ML/AI Development: Design, develop and implement computational models and workflows for optimization of recombinant protein immunotherapies, epitope discovery, and related research areas.


• Cross-Functional Collaboration: Partner with bioinformatics, immunology and scientific computing teams to deliver data-driven solutions for Nykode’s  R&D pipelines.


• Build Data Infrastructure: Develop and maintain end-to-end pipelines for the modeling and interpretation of biological and clinical data (e.g., protein modelling, immunogenicity prediction, target identification).


• Drive Innovation: Monitor emerging technologies and integrate best-in-class computational practices to keep Nykode at the cutting edge.


• Mentor & Guide: Provide technical leadership and mentorship to foster a high-performing, collaborative research culture.

Education and Training Requirements

• PhD or equivalent in computational science, bioinformatics, immunoinformatics, or a related discipline.


• Minimum two years of post-PhD experience in academia or industry.
  

Knowledge and Experience

• ML/AI Expertise: A proven track record of applying machine learning and AI to solve complex biological or biomedical challenges.


• Technical Stack: Proficiency in Python (additional languages like R is a plus), and deep learning frameworks such as PyTorch.


• Pipeline Architecture: Hands-on experience building and scaling computational pipelines (e.g., Nextflow) for large-scale biological data.


• Structural Biology & Modeling: Understanding of protein structure prediction and AI-driven modeling; experience with biological foundation models is highly preferred.


• Experience with development of computational workflows to identify candidate antigens/autoantigens using genomic, transcriptomic and/or immunopeptidomic datasets is a plus.


• Infrastructure: Experience working within cloud-computing or high-performance computing (HPC) environments.


• Communication: Fluency in English, verbal and written, with the ability to communicate complex technical concepts to non-experts.

Our Ideal Colleague We seek an innovative scientist driven by the potential of ML/AI and computational science to advance life sciences and biotechnology. Our ideal colleague demonstrates strong analytical and problem-solving skills, excels in communication and teamwork, and has a proven ability in scientific presentation and documentation. They show initiative, resourcefulness, and a collaborative spirit, thriving in multidisciplinary teams that value knowledge sharing.
Motivated by curiosity and a genuine desire to improve patient care, the right candidate is eager to advance medicine alongside a value-driven, supportive team. Commitment to lifelong learning and openness to new approaches is essential, as is enthusiasm for contributing to meaningful breakthroughs in health through cutting-edge computational science.

The Application Process

Due date: 8th of April. We look forward to receiving your application! Please note, we do not accept applications by mail. Should you have any further questions regarding the position, please reach out to [email protected] or Andreas Hoff – Director, Head of In Silico and AI Department at [email protected].