Machine Learning(Deep Learning) and Health Informatics PhD

The goal of the PhD projects will be to contribute to one or more of the existing research areas in translating health informatics data to actionable diagnostic, prognostic and treatment information while developing novel computational (machine learning, statistical, and/or optimization) approaches. The assistantship recipient will be able to work in collaboration with clinicians, industry and other researchers.

Examples of projects could be:
• Developing novel computational and analytic models and methods to identify cancer patient subtypes with the ultimate purpose of personalizing treatment strategies by integrating multiple data types (such as gene expression, somatic mutation, copy number variation, and clinical data).
• Explore how similarities in different cancers’ molecular biology can be leveraged to improve diagnostic and prognostic biomarkers and for drug repurposing.
• Develop a data-driven computational model capable of learning the abnormal and lethal brain anatomy through neonatal MRIs to detect total and regional neuroanatomical deviations.
• Developing computational models and methods to integrate learning task specific parameters and latent factors using health informatics dataset from disparate cohorts and different studies.
Qualifications In terms of education, candidates must have a Master (or equivalent) degree in computer science or a related discipline (e.g., statistics, computational mathematics, industrial engineering, operations research or management science with a specialization in data science and machine learning) and eager to become a data science and analytics researcher.

Ideally, the candidate should have some of the following qualifications:
• Strong analytical skills (e.g. statistics, probability, mathematical modeling) and programming skills in one or more languages (R, Matlab, Python, C++).
• Desired but not required qualifications are interest and knowledge in healthcare applications and publications (conference proceeding or journal article).
• Belong to the top of your graduating class as evidenced by your grades and supported by your references.
• Self-motivated, fast learner, dedicated, autonomous and creative.
• Genuine interest (or experience) in predictive analytics (data mining, machine learning, artificial intelligence) and willing to demonstrate this as part of the application process.
• Excellent analytical skills and willing to implement your ideas in software.
• Ambitious, but at the same time a team player.
• Excellent communication skills.

Admission and Enrollment Information The scholarships for the PhD degree are subject to academic approval, and the candidates will be enrolled in the Computer Science PhD program. For information about our enrollment requirements and the general planning of the PhD program, please see the WSU and CS Department PhD Guide.
We offer,
• A fully funded position with a highly competitive salary
• Working in a scientifically stimulating, innovative, dynamic, well- equipped environment
• Opportunity to work closely with cross-disciplinary academic, healthcare, and industry partners
• State-of-the-art research facilities and computational equipment
• Excellent support for post-graduation employment opportunities in academia, industry and government.

For prioritized consideration please email your application no later than 23 April 2021 to Dr. Suzan Arslanturk at gl9815@wayne.edu. Applications and enclosures received after the deadline will be considered only if the position is not filled.
Applications should include the following documents (ideally combined into one pdf document):
• Cover letter (including a brief description of past related experience and future interests, as well as the earliest possible starting date)
• A detailed Curriculum Vitae
• Grade transcripts listing course titles for all degrees (unofficial transcripts accepted)
• Scholarly publications including journal articles, conference proceedings, technical reports, theses, term papers, etc.
• Name and contact details of at least two referees
Candidates may apply prior to obtaining their master's degree but cannot begin before having received it. All interested candidates irrespective of age, gender, disability, race, religion or ethnic background are encouraged to apply.

which school I not see it

gl9815@wayne.edu ; it's wayne state university

Thank you, sounds pretty good.