Alberta Machine Intelligence Institute (Amii)’s Post

I have at least 10 individual requirements for Research Scientists right now 🔥 I'm looking for varying seniorities from the Mid ➡ Principal level 🦾 Here are the basic details: 👉 Must be SF, NY or Boston based 👉 Total Comp's ranging from $200,000 - $600,000 👉 4x different AI R&D Labs all operating into AI Drug Discovery 👉 Over half a billion in funding collectively (3x Seed, 1x Series B) What you need to be considered: 💡 Background in high-impact ML Science (PhD preferred) 💡 Demonstrable success (i.e. papers in top AI journals) in ML Research 💡 SME in one of: Deep Learning, Diffusion Modelling, LLMs, Generative AI 💡 Track record in top-tier AI Labs (Academic or industry) 💡 Motivation to work in the frontier of AI for Drug Discovery One thing I always try to make clear is that you need NO AI Drug Disc experience. In fact, even if you've never touched this area, I encourage you to get in touch 🍓🧬👀 If you think this applies to you or someone you know, please reach out 😉🧬💻 Ethan Chesterfield Richard Bilyard ☁️ Antonia Otter Dan Kettle Marco Navarro Neil Patel Josh Howlett #beyondthemodel #mlresearch #mlscience #ai #jobs

In life sciences, there's a huge amount of complex data being produced, especially with new technologies in genomics, proteomics, and other fields where researchers are generating vast amounts of data at an unprecedented rate. This mass of data can be overwhelming to analyse and interpret though. That's where AI comes in, changing and enhancing how we manage and interpret all this information. AI algorithms, particularly those involving machine learning and deep learning, are adept at processing large datasets quickly and accurately. Life Sciences, as an industry, is seeing a huge shift towards hiring talent that has a background in AI and data science to facilitate the necessary business changes that such huge amounts of data dictates. #LifeSciences #AIinScience #MachineLearning #DeepLearning #DrugDiscovery #Staffing #Recruitment

Opportunities

Want to know what the next big thing in AI for science is? #AI can be applied to many things - but one of the most impactful areas is its use in #science and scientific discovery. I have been lucky enough to work in this space inside #academia and #bigtech, and now I am at it again - this time as a co #founder of a #startup. Some might think I am crazy quitting a great job with a large company, but this is something I had to get in at the ground floor on. The next generation of drugs are already being discovered using AI - so what’s the next big thing? Well to find out what it is, you’ll have to reach out! Or even better you can join me! I am #hiring for a range of #AI, #software #engineering and #simulation positions to join our stealth mode AI for science company. If you wish to work on what I truely believe is one of the most important applications of AI in the world today, take a look at our openings: https://lnkd.in/eWKMsjN3 I can promise you will be working with some of the brightest minds and highest achievers I have the pleasure to know. #AI #Science #Bioinformatics #NowHiring #Oxford #Manchester #InnovationDriven

Hiring Alert: Lead the Future of Drug Discovery with Us! At Receptor.AI, we're leading the next generation of drug discovery with cutting-edge multiplatform ecosystem. Our expert team is at the forefront of TechBio, and we're seeking exceptional professionals to join us. 𝟭. 𝗦𝗲𝗻𝗶𝗼𝗿 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗵𝗲𝗺𝗶𝘀𝘁 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: Proven success in leading in silico campaigns, from virtual screening to IND enablement in drug discovery projects, including developing generative AI models for de novo compound design and structure-based ML models for virtual screening. 𝗦𝗸𝗶𝗹𝗹𝘀: Proficiency in building AI-based drug discovery workflows using advanced computational chemistry tools for virtual screening, molecular docking, and pharmacophore modeling. 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: Success in advancing compounds from hit identification to lead optimization in commercial drug discovery projects, with contributions to IND submissions and patent filings. 𝟮. 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗿 – 𝗗𝗿𝘂𝗴 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱: Extensive experience managing large-scale AI drug discovery or biotech projects at the preclinical stage. 𝗦𝗸𝗶𝗹𝗹𝘀: Proficient in managing multiple projects in parallel, analyzing experimental data, and providing strategic oversight of AI-driven projects. 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲: Leading interdisciplinary teams, especially in rapidly advancing fields like AI drug discovery and biotech; engaging with pharmaceutical companies, regulatory bodies, advisors, and internal stakeholders to communicate progress, challenges, and outcomes. 𝟯. 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗟𝗲𝗮𝗱 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗣𝗿𝗼𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Expertise in Python and Django for scalable back-end development, with a strong focus on building and deploying complex machine learning pipelines, including deep learning architectures (e.g., Diffusion Neural Networks, Transformers, GANs). Proven experience with large language models (LLMs), advanced data handling for big data, and high-performance computing (HPC) for large-scale simulations. 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗗𝗲𝘀𝗶𝗴𝗻: Extensive experience designing complex systems, including microservices and distributed architectures with Docker and Kubernetes, and optimizing database structures (SQL, NoSQL, Graph Databases). 𝗗𝗲𝘃𝗢𝗽𝘀 & 𝗖𝗹𝗼𝘂𝗱: Expert in AWS, GCP, or Azure, with proficiency in CI/CD processes for efficient software delivery. 💡 Interested? We look forward to welcoming talented individuals to our technology-driven team! To apply or learn more about these positions, please contact ai@receptor.ai Join us and shape the future of drug discovery! #hiring #drugdiscovery #ai #biotech #innovation #medicinalchemistry

In this market, finding good AI talent is hard. Luckily BAIR is here to make your life easier! They've helpfully compiled a list of our newest graduates that are entering the market. If you're hiring, please give them a look!

I have multiple Ph.D. openings in my team (AI4D Lab) focusing on the industrialization of AI and scientific machine learning for engineering designs and large-scale optimizations. Folks, I would appreciate it if you could spread the word by reposting or introducing those who might be interested in earning a Ph.D. under my supervision. #phd #phdposition #AI #machinelearning #fluiddynmaics #computing

Take a look at one of our latest roles! Senior Researcher in Network System Design for AI, 130-180k CHF + Bonus scheme - #Switzerland. Interested? Click the link to apply #DataScience #DeepLearning #ICResources #NLP #DataEngineering #3DReconstruction #TechnologyRecruitment #AI #TechnologyCareers #TechnologyJobs #Robotics #MachineLearning #ImageProcessing #ComputerVision #ArtificialIntelligence #Graphics #Software

Job opportunity! Lead Researcher in Network System Design for AI, 170-250k CHF + bonus scheme - #Switzerland. To find out more, please visit the link below #AI #Software #DataScience #ImageProcessing #Robotics #ComputerVision #3DReconstruction #ICResources #TechnologyRecruitment #NLP #DeepLearning #TechnologyCareers #MachineLearning #TechnologyJobs #ArtificialIntelligence #Graphics #DataEngineering

How does data science contribute to healthcare and medical research? - Data science enables analysis of electronic health records (EHRs) and medical data to extract valuable insights for research and patient care. - Predictive modeling and machine learning algorithms help identify patterns and predict disease outcomes, aiding in early diagnosis and personalized treatment. - Data scientists utilize data mining techniques to uncover hidden relationships between genetic, environmental, and lifestyle factors and their impact on health. - Clinical decision support systems leverage data science to provide evidence-based recommendations to healthcare providers, improving diagnostic accuracy and treatment decision-making. - Data science facilitates drug discovery and development by analyzing large-scale genomic and molecular data, identifying potential targets, and optimizing drug efficacy. - Public health surveillance systems use data science to monitor disease outbreaks, track population health trends, and facilitate proactive interventions. - Health monitoring devices and wearables generate vast amounts of data, which data scientists analyze to provide real-time health insights and enable remote patient monitoring. - Data science contributes to precision medicine by integrating patient data, genomics, and clinical information to tailor treatment plans based on individual characteristics. - Natural language processing (NLP) techniques enable extraction and analysis of information from medical literature, supporting medical research and evidence-based practice. - Data science enhances healthcare operations by optimizing resource allocation, scheduling, and workflow management, leading to improved efficiency and patient outcomes. Do you need help writing your resume/CV, cover letter or optimizing your LinkedIn profile? Contact me now. Let us do this! Visit my website: www.yourresumeexpert.com #resume #resumewriting #resumewritingservices #cv #cvwriting #cvwritingservices #linkedinprofile #linkedinprofileoptimization #jobsearch #jobopportunity #jobvacancy #jobinterview #jobsearching #careergrowth #careerdevelopment #careeropportunities #interview #softwareengineerresume #datascience #dataanalyst #computerscience #executiveresumes