Experience with analytic methods and technologies (artificial intelligence, machine learning/ deep learning/ neural networks, natural language processing, visualizations) Demonstrated proficiency with data science languages (R, Python, SQL, Julia, SAS) and visualization tools (Tableau, Spotfire, SAS, JMP, RShiny.

Development and application of machine learning algorithms for structural biology, including protein design. To accomplish this, we continue to be deeply rooted in science and academic research while also having built a fully integrated, global immunotherapy company with cGMP and GMP manufacturing facilities anchored around deep expertise in immunology and complemented by an expanding set of capabilities.

PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR.

We are looking for students who are self-motivated and interested in signal/image processing, machine learning, deep learning, statistical pattern recognition, and high-performance computing.

You are familiar with AWS services such as S3, EC2, ECS, AWS Batch, and Sagemaker to reduce runtime for training and evaluating deep learning models. Lead development and productionize cloud-based machine learning pipelines for small molecule discovery problems, including property prediction, target-ligand interaction prediction, and toxicology screening.

Deep knowledge of HR, People Ops, DEI and Organizational Development (OD) best practices rooted in equity and justice nd demonstrated commitment to continuous learning and development. A skilled people manager and leader who models integrity, accountability, trustworthiness, and empathy with deep self-awareness and emotional intelligence.

Practical experience with deep learning frameworks, such as TensorFlow or PyTorch. Proficiency in programming languages such as Python and R, with experience in data analysis and machine learning libraries.

Hands-on experience with machine learning (including deep learning), and one or more of the following technical areas: computer vision and image processing, multi-modal large language models, speaker identification/verification technologies.

We achieve this by offering strong academic, co-curricular, and social-emotional learning that prepares students for success in college and beyond. You'll conduct a deep exploration of daily content in order to guide students to analyze books by authors like James Baldwin, Toni Morrison, F. Scott Fitzgerald, William Shakespeare, and Yaa Gyasi; books that ignite a passion for literature, sharpen a critical eye for examining the world, and deepen students’ intellectual identity.

Deep Learning Research: Stay at the forefront of deep learning research and methodologies, applying innovative techniques to address challenges in NLP tasks, such as named entity recognition, sentiment analysis, language translation, and more.

Demonstrated experience with machine learning algorithms (regression, semi-supervised learning, deep learning, reinforcement learning, time series analysis, predictive modeling, data mining, cognitive computing.

Deep understanding of the entire software development life cycle and common life science tools. PHD candidates in Engineering/ IT/Computer Engineering/Computer Science/Bioinformatics or related discipline with relevant with a minimum of 1 years of experience in software development and pipeline automation in the pharmaceutical and/or biotech industry.

This position is ideal for someone with broad expertise in machine learning, deep learning, and computational sciences who is looking to join a very dynamic and innovative environment and pioneer the next frontier of innovation, application, and human-computer interactions enabled by generative models.

Deep expertise in Ethics, Bioethics or Technology Ethics and PrivacyExperience with Data Privacy (DP) controls implementation, Data/Digital Ethics risks management preferred. Deep understanding to support the business on the key areas of data and digital ethics and compliance such as data privacy, data ethics, AI ethics including technology ethics to enable sustainable and responsible innovation.

Minimum of three years' experience building production NLP and deep learning models using PyTorch/Tensorflow, along with using large language model architectures (BERT, GPT-3 etc.) Position Description:As a Senior Data Scientist, you will collaborate with the Data Science and Machine Learning team and will create data science, machine learning, and AI solutions to better address the needs of our constituents (students, alumni, faculty, researchers, staff, and community at large.