WHY UT SOUTHWESTERN?
With over 75 years of excellence in Dallas-Fort Worth, Texas, UT Southwestern is committed to excellence, innovation, teamwork, and compassion. As a world-renowned medical and research center, we strive to provide the best possible care, resources, and benefits for our valued employees. Ranked as the number 1 hospital in Dallas-Fort Worth according to U.S. News & World Report, we invest in you with opportunities for career growth and development to align with your future goals. Our highly competitive benefits package offers healthcare, PTO and paid holidays, on-site childcare, wage, merit increases and so much more. We invite you to be a part of the UT Southwestern team where you’ll discover a culture of teamwork, professionalism, and a rewarding career!

JOB SUMMARY

We are seeking a skilled and highly motivated full-time Machine Learning Research Scientist to join our innovative team in the Departments of Neurology and Bioinformatics. This role entails developing and applying machine learning and NLP techniques to analyze extensive audio datasets and transcribed text, aiming to identify predictive markers of dementia progression. The successful candidate will play a pivotal role in our groundbreaking research into dementia, working closely under the close mentorship of several faculty, including Prof. Ihab Hajjar, MD, an authority in dementia, and Prof. Albert Montillo, PhD, a renowned machine learning expert.

·       Access to Large Multiyear Datasets

o   You will have access to one of the most extensive multiyear datasets available in the field, providing a rich foundation for impactful research.

·       High-Performance Computing Resources

o   Leverage one of the largest high-performance compute clusters, facilitating advanced computational experiments and model training at an unprecedented scale.

·       Advanced Machine Learning Development for audio analysis

o   Design and implement algorithms to extract features from audio recordings that indicate dementia.

o   Utilize cutting-edge machine learning techniques to analyze large-scale audio data for pattern recognition and feature extraction.

·       Natural Language Processing (NLP) on Transcribed Text

o   Employ NLP methods on transcribed speech to identify linguistic markers related to dementia progression.

o   Develop models to correlate changes in speech patterns, vocabulary, and syntax with dementia stages.

·       Predictive Modeling for Dementia Progression

o   Design, train, and validate machine learning models using large datasets.

o   Ensure models are robust, scalable, and accurately predict dementia progression scores.

·       Collaboration and Research

o   Work under the mentorship of Prof. Hajjar and Prof. Montillo, contributing to and leading interdisciplinary research initiatives.

o   Collaborate with a team of experts in a dynamic, innovative research environment.

Laboratory Expectations

·       Proficiency in NLP, with experience in text analysis, language modeling, and sentiment analysis. Experience with one or more modern NLP frameworks and tools (e.g., Transformers library, NLTK, SpaCy, BERT, AllenNLP, Gensim), is a strong plus.

·       Expertise in programming languages such as Python, R, or Java, and familiarity with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

·       Experience with data preprocessing, feature extraction, and model validation techniques.

·       Experience in biomedical data analysis or working on healthcare-related machine learning projects.

·       Familiarity with audio processing libraries (e.g., LibROSA, AudioKit, Kaldi, PyAudio, SpeechRecognition, Praat, Wav2Vec).

Preferred Skills and Qualifications

·       PhD in Computer Science, Data Science, Engineering, Statistics, or a related field with a focus on machine learning.

·       Strong background in machine learning, including supervised and unsupervised learning, and deep learning.

·       Experience in biomedical data analysis or working on healthcare-related machine learning projects.

·       Strong statistical analysis skills and experience working with large, complex datasets.

·       Excellent problem-solving abilities and attention to detail.

·       Knowledge of high-performance computing technologies (Linux) and batch scheduling and/or cloud computing for big data experiments (SLURM, Ray, Hadoop, Spark).

·       Demonstrated ability to work in interdisciplinary teams and strong communication skills for conveying complex concepts to non-technical stakeholders.

·       Publications in relevant scientific journals and a track record of successful research projects.

BENEFITS
UT Southwestern is proud to offer a competitive and comprehensive benefits package to eligible employees. Our benefits are designed to support your overall wellbeing, and include:

• PPO medical plan, available day one at no cost for full-time employee-only coverage
• 100% coverage for preventive healthcare-no copay
• Paid Time Off, available day one
• Retirement Programs through the Teacher Retirement System of Texas (TRS)
• Paid Parental Leave Benefit
• Wellness programs
• Tuition Reimbursement
• Public Service Loan Forgiveness (PSLF) Qualified Employer
• Learn more about these and other UTSW employee benefits!

EXPERIENCE AND EDUCATION
Required

• Education
  PhD with major course work in the field of assignment or
  Master’s Degree with major course work in the field of assignment or
  Bachelor’s Degree with major course work in the field of assignment

• Experience
  5 years of research experience in the field of assignment with PhD including
  2 years at the level of Senior Research Associate or its equivalent or
  7 years of research experience in the field of assignment with Master’s degree including
  3 years at the level of Senior Research Associate or its equivalent or
  9 years of research experience in the field of assignment with Bachelor’s degree including
  4 years Level of Senior Research Associate or its equivalent.

JOB DUTIES

• Plans, organizes coordinates, directs, and personally participates in assigned scientific or medical research project. Selects or assists in selection of key research personnel. Determines specific goals or objectives to be attained. Assigns and reviews work of subordinates. Plans experimental protocols.
• Reviews and analyzes resulting research data. Revises techniques or approaches to work problems as indicated necessary by research data.
• Compiles, writes, and submits research results to supervisor. Prepares or assists in preparation of research papers, reports, and abstracts for publication as one of co-authors.
• Designs, develops, or adapts equipment used in experiments or research to obtain desired results.
• Plans and supervises training of technicians and other laboratory personnel with respect to proper laboratory techniques, use of laboratory equipment, and safety procedures.
• Supervises group of employees of lower grade engaged in performance of technical and professional work, which vary from routine to complex laboratory work tasks.
• May confer with industrial, governmental, or other groups concerning progress or results of research project.
• Performs other duties as assigned.

SECURITY AND EEO STATEMENT
Security
This position is security-sensitive and subject to Texas Education Code 51.215, which authorizes UT Southwestern to obtain criminal history record information. To the extent this position requires the holder to research, work on, or have access to critical infrastructure as defined in Section 113.001(2) of the Texas Business and Commerce Code, the ability to maintain the security or integrity of the critical infrastructure is a minimum qualification to be hired and to continue to be employed in the position.

EEO Statement
UT Southwestern Medical Center is committed to an educational and working environment that provides equal opportunity to all members of the University community. As an equal opportunity employer, UT Southwestern prohibits unlawful discrimination, including discrimination on the basis of race, color, religion, national origin, sex, sexual orientation, gender identity, gender expression, age, disability, genetic information, citizenship status, or veteran status.