The posting
You design and benchmark novel machine learning algorithms for complex biological problems, working at the intersection of causal representation learning and drug discovery.
## Tasks - Design, implement and benchmark ML algorithms using causal representation learning and out-of-distribution generalization - Frame foundational research questions beyond off-the-shelf ML paradigms for drug discovery - Collaborate with cross-functional research teams across global innovation hubs - Build and scale neural network architectures using deep learning frameworks - Translate biological challenges into rigorous computational models - Author scientific publications for top-tier ML and computational biology venues - Present research findings at internal symposia and international conferences
## Profile - Ph.D. (or exceptional Master's degree) in Computer Science, Statistics, Applied Mathematics, Computational Biology, Physics or related field - Solid grounding in machine learning theory, with interest in causal representation learning or out-of-distribution generalization - Hands-on expertise building and training deep neural networks, proficiency with modern deep learning frameworks - Track record of publications at premier ML conferences or journals - Interest in working with biological datasets and molecular systems - Strong collaborative and interpersonal skills across distributed global teams
## Company Pharmaceutical research
Apply online via Try&Hire with your profile — https://tryandhire.io/ch-en/jobs/e/senior-machine-learning-scientist-tah-l254l/



