Senior AI Scientist

<p><b><span>Senior AI Scientist</span><span> </span><span>(Fundamental AI Research for Science)</span><span>, Location – Barcelona (Spain)</span></b><span> </span></p><p><span> </span></p><p><b><span>Introduction to the opportunity:</span></b><span> </span></p><p><span><span>Are you passionate about creating artificial intelligence and machine learning models, algorithms, and tools for real-world science applications? Does contributing to preventing, </span><span>modifying</span><span>, and even curing some of the world's most complex diseases inspire you? Would you like to work on designing and developing an iterative drug discovery and development process while drawing on methods across various fields, from active learning to optimisation and search? What about advancing our understanding of biology, streamlining research and development processes, and </span><span>leveraging</span><span> a variety of data modalities? Do you thrive working in a supportive, inclusive environment where creativity, collaboration across disciplines and lifelong learning towards innovative breakthroughs are encouraged? If yes, this opportunity may be for you. </span></span><span> </span></p><p><span> </span></p><p><span><span>Join our interdisciplinary Centre for Artificial Intelligence team working on the next generation of medicines and vaccines at the intersection of AI, biology, and engineering. Your work will contribute to transforming the drug discovery and development value chain as we know it, uncovering novel biological insights, automating processes, streamlining decisions, and improving the overall pipeline across all therapeutic areas at AstraZeneca</span><span>.  </span><span>   </span></span><span> </span></p><p><span> </span></p><p><b><span><span>Accountabilities:    </span></span></b><span> </span></p><p><span><span>•You will work efficiently in a team to deliver projects optimally, developing and using the latest AI/ML methods, approaches, and techniques, with engineering best practices and standard processes for various biology, </span><span>chemistry</span><span> and clinical problems</span><span>.  </span><span> </span></span><span> </span></p><p><span> </span></p><p><span><span>•You will be part of multifunctional teams to conceive, design, develop and conduct experiments to test hypotheses, </span><span>validate</span><span> </span><span>new approaches</span><span>, and compare the effectiveness of different AI/ML algorithms, </span><span>methods</span><span> and tools for discovering, designing, and optimising molecules with improved biological activity</span><span>.  </span><span> </span></span><span> </span></p><p><span> </span></p><p><span><span>•You will contribute to addressing challenges and opportunities in the drug discovery and development value chain processes and provide innovative solutions in fields such as deep learning, representation learning, reinforcement learning, meta-learning, active learning approaches applied to de novo </span><span>molecule </span><span>design, protein engineering, in-silico discovery, structural biology, computational biology, translational sciences, </span><span>biomarker discovery</span><span>, </span><span>clinical research</span><span>, clinical trials</span><span> and many other <span>areas.    </span></span></span><span> </span></p><p><span> </span></p><p><span><span>•You will </span><span>develop</span><span> machine learning models designed explicitly for analysing heterogeneous biological data while collaborating with biology researchers to run algorithmically designed wet lab experiments to inform future experimental directions</span><span>.  </span></span><span> </span></p><p><span> </span></p><p><span><span>•You will remain at the forefront of AI/ML research by </span><span>participating</span><span> in journal clubs, seminars, mentoring, and personal development initiatives and contributing to publications and academic and industry collaborations.</span></span><span> </span></p><p><span> </span></p><p><b><span>Essential <span>Skills/Experience:    </span></span></b><span> </span></p><p><span><span>•</span><span>A PhD in machine learning, statistics, computer science, mathematics, physics, or a related technical discipline </span><span>and </span><span>with relevant fundamental research experience </span><span>in artificial intelligence and machine </span><span>learning</span><span> OR</span><span> MSc with a few years of relevant </span><span>experience in the research and development of artificial intelligence and machine learning approaches to life sciences applications.</span></span><span> </span></p><p><span> </span></p><p><span><span>•</span><span>Fundamental AI research experience</span><span> and w</span><span>ell-rounded h</span><span>ands-on a</span><span>bility to understand and implement AI/ML techniques based on publications or developed entirely in-house. </span><span>In addition, e</span><span>xperience in</span><span> applying rigorous