Join Dr. Sikora’s lab at the forefront of developing and integrating cutting-edge natural language processing (NLP) and artificial intelligence (AI) to revolutionize real-world applications in medicine and health. This role offers a unique opportunity to be part of a pioneering team that develops advanced AI solutions to tackle some of the most pressing challenges in healthcare. As a Data Scientist (NLP/AI) in our lab, you will be instrumental in advancing language technologies that improve the accuracy and efficiency of medical diagnostics and patient care documentation. This position not only allows you to contribute to meaningful and transformative projects but also to grow professionally in a dynamic, interdisciplinary environment.

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Day-to-day, you will be immersed in a variety of exciting projects, such as enhancing and evaluating large language models (LLMs) for diagnostic decision-making, optimizing LLM training for low-resource environments, and assessing model explainability. You'll work closely with a team of graduate students, postdocs, and other collaborators to develop innovative AI models, create software tools, and establish robust data processing pipelines. Your contributions will directly impact our ongoing efforts to transform healthcare through AI, making this role crucial to the success of our department and the broader university community.

Key Responsibilities:

• Conduct comprehensive literature reviews to identify existing solutions and their limitations and develop advanced NLP algorithms for multimodal data.

• Design and conduct experiments to validate hypotheses using applied statistics, clean and preprocess data for model training, and debug code to analyze complex datasets.

• Develop reproducible research pipelines and maintain thorough documentation on GitHub.

• Assist the Principal Investigator (PI) with grant writing and the development of research proposals.

• Present research findings and progress at lab and collaborative meetings, also prepare and submit manuscripts and abstracts for publication in scientific journals and conferences.

• Support lab members and collaborators with research tasks and manage lab logistics, including the lab website and server infrastructure.

• Adhere to responsible conduct of research guidelines, participate in ethics training sessions, and monitor compliance with research ethics.

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Minimum Qualifications:

Entry Professional:

• Bachelor's degree in Computer Sciences, Data Science or related field.

  • A combination of education and related technical/paraprofessional experience may be substituted for the bachelor’s degree on a year for year basis.

Intermediate Level:

• Bachelor's degree in Computer Sciences, Data Science or related field.

  • A combination of education and related technical/paraprofessional experience may be substituted for the bachelor’s degree on a year for year basis.

• One (1) year of related natural language processing and artificial intelligence experience.

• One (1) year of experience with NLP/deep learning frameworks such as PyTorch and TensorFlow.

• One (1) year of experience with NLP state-of-the-art models (BERT, Llama, Mistral, etc.).

• One (1) year of experience with training models on GPUs.

• One (1) year of experience working with Unix and/or Linux, including shell scripting.

Senior Level: 

• Bachelor's degree in Computer Sciences, Data Science or related field.

  • A combination of education and related technical/paraprofessional experience may be substituted for the bachelor’s degree on a year for year basis.

• Two (2) years of related natural language processing and artificial intelligence experience.

• Two (2) years of experience with NLP/deep learning frameworks such as PyTorch and TensorFlow.

• Two (2) years of experience with NLP state-of-the-art models (BERT, Llama, Mistral, etc.).

• Two (2) years of experience with training models on GPUs.

• Two (2) years of experience working with Unix and/or Linux, including shell scripting.

Principal Level:

• Bachelor's degree in related Computer Sciences, Data Science or related field.

  • A combination of education and related technical/paraprofessional experience may be substituted for the bachelor’s degree on a year for year basis.

• Three (3) years of related natural language processing and artificial intelligence experience.

• Three (3) years of experience with NLP/deep learning frameworks such as PyTorch and TensorFlow.

• Three (3) years of experience with NLP state-of-the-art models (BERT, Llama, Mistral, etc.).

• Three (3) years of experience with training models on GPUs.

• Three (3) years of experience working with Unix and/or Linux, including shell scripting.

Applicants must meet minimum qualifications at the time of hire.

Preferred Qualifications:

• Documented opensource contributions.

• Experience with biomedical data.

• One (1) to four (4) years of experience with cloud-based computing solutions (AWS, Google Cloud Platform, etc.).

• One (1) to four (4) years of experience developing NLP/deep learning frameworks such as PyTorch and TensorFlow.

• One (1) to four (4) years of experience with NLP state-of-the-art models (BERT, Llama, Mistral, etc.).

• One (1) to four (4) years of experience implementing NLP/AI algorithms and models for real-world applications.

Knowledge, Skills, and Abilities:

• Ability to communicate effectively, both in writing and orally.

• Ability to establish and maintain effective working relationships with employees at all levels throughout the institution and with geographically distributed collaborators.

• Demonstrated commitment and leadership ability to advance diversity and inclusion.

• Advanced knowledge of NLP and AI principles, including concept in computational linguistics, neural networks, deep learning, searching algorithms.

• Advanced knowledge of basic statistical principles relevant in medical research.

• Ability to clearly document code.

• Ability to analyze and solve complex problems and apply quantitative analytical approaches.

• Demonstrated proficiency in Python, with a focus on NLP frameworks such as Transformers, spaCy, and expertise in training large language models (LLMs) on GPUs, including skills of prompting, fine-tuning methodologies such as full fine-tuning, using Adapters, and applying LoRa.

• Ability to interact with people of varying technical levels to gather requirements and understand existing systems relevant to the challenges at hand.

• Ability to interact effectively and respectfully in a team with complementary competencies.

For full consideration, please submit the following document(s):

1. Curriculum vitae / Resume

2. Links to 1-3 source code repositories with open source contributions, if applicable. 

3. Three to five professional references, including name, address, phone number (mobile number if appropriate), and email address.