As Lead Scientist Generative Protein Design at Bio-LogX you will join our research team in our lab in Vienna and help us bring next generation drugs from the bench into the clinic.
Your main responsibilities will be.
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Establish workflows to design proteins de-novo based on the latest available deep learning tools (RFdiffusion, BoltzGen, BindCraft), including secure cloud environment setup (e.g. Docker, Terraform).
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Adapt and extend open-source generative tools with a modular in silico filter pipeline for multi-dimensional candidate pre-screening, to fulfil drug target specifications. Architect the design-filter loop to optimize compute time.
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Design and optimize binders, enzymes and full multi-domain proteins for therapeutic targets according to research target profile specifications, closely collaborate with protein production and functional characterization teams to iterate towards final sequence.
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Take appropriate make-or-buy decisions for the generative protein design workflow
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Maintain fully documented setup. Enable non-computational scientists to run standard design campaigns; stay current with the fast-moving protein design literature and evaluate new tools for integration
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Engage with other managers at Bio-LogX to interpret results and define next steps, regularly participate in reviewing and advancing the overall program strategy.
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Motivate, coach, mentor, give feedback to, develop team members.
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Documentation of results according to the Bio-LogX R&D Quality Standards, to ensure the quality of results and their documentation are acceptable for sharing with other teams, preparing reports, patenting, etc.
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Drafting of patent claims as appropriate, publication of selected results in scientific journals
What you have to offer.
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Ph.D. (or equivalent track record) in computational biology, bioinformatics, structural biology, or biochemistry with at least 3 years of relevant work experience following your PhD in a biotech or pharma setting.
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Hands-on experience with at least two generative design tools and molecular dynamics simulations: BindCraft, RFdiffusion, BoltzGen, ProteinMPNN, or equivalent
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Strong Python programming skills, including building bioinformatics pipelines and integrating third-party command-line tools programmatically
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Familiarity with cloud GPU computing (AWS or equivalent): launching instances, working with Docker containers, basic Linux/bash scripting
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Working knowledge of protein therapeutics developability — understanding why sequence liabilities, aggregation, and T-cell epitopes matter in a drug development context
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Ability to read, adapt, and contribute to scientific codebases (Python/PyTorch); comfort working from preprints and GitHub repositories
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Strong communication skills — able to translate computational outputs into actionable recommendations for biologists
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Comfortable in a fast-paced environment and able embrace change, while working to produce key deliverables in accordance with project timelines.
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Proactive, self-motivated team player with strong interpersonal skills, appropriate sense of urgency and the ability to work independently.
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Proficiency in English (written and spoken).
Benefits for you.
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Take responsibility for a key research field within Bio-LogX.
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Lead and develop a team of highly skilled bio-informaticians, scientists and researchers.
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Pioneer new methods and processes to industrialize key research techniques.
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Be part of a highly motivated, multinational and fun team that believes protein based modalities can become next-generation medicines for patients.
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A competitive compensation package that reflects the qualifications and seniority of the candidate and may include further, e.g. performance-based, incentives. Due to legal requirements, we are required to state that the minimum salary for this job is a monthly salary of EUR 5.500,- gross.
Bio-LogX, recently founded by BioNTech R&D Austria’s leadership team, is a VC-backed translation & innovation engine based at the Vienna Biocenter. We develop drug candidates from animal to clinical proof of concept – always with the ambition to transform the standard of care. We are agnostic about the therapeutic area but focus on protein modalities: antibodies, enzymes, fusions, engagers, degraders, agonists, antagonists.
