Applies machine learning techniques to research problems in the life sciences with an emphasis on using computational approaches for building predictive models in a variety of contexts including biomedical images, genomics and clinical datasets. Design brain-inspired, data-efficient learning algorithms to detective patterns in a wide range of data modalities such as image, text, sequence, time series, and large-scale experimental measurements. Participates in interdisciplinary collaborations. Reports on results of research including publishing scholarly papers in scientific journals, giving presentations at symposia, conferences, meetings, and seminars. Participates in the preparation of reports and proposals required by funding agencies to obtain and continue funding support.
* Expertise in Python and/or C/C++ with the ability to design and write quality code. * Bachelor's degree or equivalent. * Experience in machine learning frameworks such as PyTorch, TensorFlow or Keras. * Experience with data analysis. * Candidates with experience in spiking neural networks or neuromorphic hardware is preferred. * Strong knowledge of algorithm design. * Knowledge of neuroscience, math and/or statistics. * Collaborative skills, including the ability to work well with scientists at other laboratories, universities, and in industry.
As an equal employment opportunity and affirmative action employer, Argonne National Laboratory is committed to a diverse and inclusive workplace that fosters collaborative scientific discovery and innovation. In support of this commitment, Argonne encourages minorities, women, veterans and individuals with disabilities to apply for employment. Argonne considers all qualified applicants for employment without regard to age, ancestry, citizenship status, color, disability, gender, gender identity, genetic information, marital status, national origin, pregnancy, race, religion, sexual orientation, veteran status or any other characteristic protected by law.
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