Deep Learning Scientist, Protein Design

Computational Protein Design Virtuoso Wanted Aikium - Where Passion Meets Purpose Aikium Inc. is revolutionizing AI-driven protein engineering, shifting the paradigm from cherry-picked top-10 evaluation to ultra-large design-library screening. Our groundbreaking Yotta Display platform enables the synthesis and experimental screening of trillion-protein libraries, pushing the boundaries of what's possible in protein design. Our internal pipelines focus on SeqRs, our patented non-antibody disorder binding protein scaffold for targeting multi-pass membrane proteins. Expansion to several scaffolds and diverse targets is under way to support our growing internal pipeline and numerous external partnerships. We're seeking a visionary leader to spearhead the development and application of cutting-edge deep learning approaches for engineering all therapeutically relevant protein scaffolds. Your Expertise Advanced Qualifications: Ph.D. in the computational sciences 2 years of hands-on deep learning experience in protein engineering / design Proven track record in developing one or more of the following: Large Language Models over biological sequence data Geometric deep learning over protein structures Diffusion-based models for any class of biomolecules Solid foundations: Comprehensive knowledge of computational methods, toolkits, and databases in protein sciences Strong understanding of therapeutic protein development objectives Familiarity with traditional bioinformatics, Next Generation Sequencing and molecular dynamics simulation Exposure to data from different types of experiments for prosecuting protein-protein interactions Special Attributes: Critical thinking and advanced analytical skills Passion for tackling complex, seemingly intractable problems Pragmatic approach to meeting milestones and getting things done Why Aikium? Be an early driver at a field-defining startup chasing the hard problems Access to one-of-a-kind synthetic biology platform that can generate labeled data at scale Founded by an experienced and grounded multi-disciplinary team Competitive compensation with generous stock options