Postdoctoral Position in Computer Science, Economics, Statistics, Computational Linguistics, Bioinformatics, Cognitive Science

University of Chicago

United States

Postdoctoral (Scholar or Fellow) Position Open in the Thirty Million
Words Center for Early Learning + Public Health.
Areas of expertise: Computer Science, Economics, Statistics, Computational
Linguistics, Bioinformatics, Cognitive Science
Start date: Flexible, ideally by Fall 2021
Application Deadline: April 1, 2021

The TMW Center for Early Learning + Public Health is a joint venture between The University of
Chicago Biological Sciences Division and the Division of the Social Sciences. It implements and
evaluates evidence-based interventions designed to promote young children's cognitive and
social-emotional development, with a priority on families living in poverty. To that end, the
TMW Center has developed an expertise in the analysis of children's early experiences and
environments. Using innovative technological tools and natural language processing methods,
the Center collects and analyzes thousands of hours of audio and video recordings of parentchild
interactions.

Additionally, the Tech team is currently developing a new wearable technology to better measure
the properties of children's natural linguistic environments and
assess the impact of parent talk on brain development. Along with those unique data, the
Center also collects extensive sociodemographic data, parental belief data and assessments of
children's skills, allowing for a broad range of analyses of early disparities and their drivers.
The role of the Postdoctoral scholar in the TMW Center will be twofold. It will first consist in
building a research agenda that leverages new advances in machine learning areas such as
Natural language processing, Sentiment analysis, Gesture, Emotion and Activity recognition to
explore the audio and video recordings of parent-child interactions. The definition of this new
agenda will entail close collaboration with the Research Analysis team - an interdisciplinary
group of researchers from Developmental Psychology, Education, Medicine, Economics, and
Computer Science – and will be supervised by Dr. Dana Suskind and Dr. John List. The
Postdoctoral scholar will also be in charge of developing state-of-the-art processing tools to
characterize the variability of parenting styles and children's experiences and relate it to the
variability of early trajectories. The position requires strong skills in machine learning and deep
learning methods, application, and architecture. Familiarity with classification and prediction
models is expected. It is anticipated that this postdoctoral opportunity will necessitate at least
two years to garner successful proficiency.

Responsibilities

1) Develop possible solutions using standard and custom procedures to prepare and analyze
the audio and video data with a moderate level of direction.
2) Keep abreast of new advances in machine learning, with a focus on deep learning, including
but not limited to Natural language processing, Sentiment analysis, Semantic analysis, Gesture,
Emotion and Activity recognition.
3) Provide guidance in the creation of research experiments relying on recordings of children's
linguistic environments.
4) Assist in the management of audio and video recordings to ensure the rigor and quality of
the data.
5) Work collaboratively with TMW Center's Project Managers, Research and Tech teams to
conduct studies.
6) Write research articles and contribute to their dissemination via publications and
participation in conferences.
7) Collaborate across disciplines and communicate methods and findings to non-specialized
team members.

Education, Experience, and Qualifications

Applicants must have a Ph.D. in Computer Science, Economics, Statistics, Computational
Linguistic, Bioinformatics, Cognitive Science or other related fields, and a strong commitment to
research. The ideal candidate is a creative thinker, problem solver and excellent programmer
with experience in the processing and analysis of audio, video and natural language data
specifically. (S)he needs to be able to learn the most important components of a subject
matter, understand the open questions in the field, and identify the data and experiments
required to find answers to those questions.

Applicants must be able to handle multiple research projects simultaneously, take initiative and
exercise independent judgment. Interdisciplinary experience is a plus, especially in education,
developmental psychology, linguistics and applied public health fields.

Technical Knowledge/Skills

1) Programming Languages: Python
2) Large scale tools: Spark or Dask (rapids.ai is a bonus)
3) Core ML: Jupyter, Scikit-learn, Numpy, Pandas
4) NLP Tools: Spacy, NLTK or CoreNLP
5) Deep learning frameworks: Tensorflow or Pytorch (preferred)
6) Experience with Deep Learning Video and Image Analysis
7) Experience with Linux command line and High-Performance Computing is a plus
8) Experience with cloud resources such as Amazon Web Services is a plus
9) Experience with GIT and experiment version control approaches is a plus

Motivated candidates should submit a curriculum vitae and a statement of research goals to
Andy Lewis at andrewlewis@bsd.uchicago.edu. Compensation in the Biological Sciences
Division follows the NIH NRSA Stipend scale. Additional information on benefits and being a
postdoc in the University of Chicago Biological Sciences Division can be found at
bsdpostdoc.uchicago.edu.


In your application, please refer to Polytechnicpositions.com

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