phd in health informatics in germany

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Doctoral degree in Public Health or PhD in Health Data Sciences

In the area of Public Health, you have different options:

• PhD within the framework of the structured PhD program Health Data Sciences
• Individual doctorate (Dr. med, Dr. rer. medic.), supervised by IPH staff
• PhD (Dr. PH) in the doctoral program of the TU Berlin, department of Management in Healthcare

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Doctorates and PhD Programs

PhD Health Data Sciences The newly established PhD program Health Data Sciences is designed for qualified young scientists who would like to deepen their methodological knowledge in the fields of biostatistics, epidemiology, meta-research, population health science, or public health and further expand their competence in research and teaching. Information on the structured PhD program in Health Data Sciences (HDS) can be found on the website . 

Individual doctorate Students studying medicine at Charité - Universitätsmedizin Berlin or at another institution can apply for a doctorate at the IPH. Unfortunately, however, our staff capacities for supervising doctoral students at the IPH are limited. Publications in scientific journals are the declared goal of an individual doctorate at the IPH. If you are interested in an individual doctorate in the field of Public Health / Epidemiology, please send your request with a d etailed description of the study project and your curriculum vitae to Dr. Toivo Glatz .

Doctorate (Dr. Public Health) Please refer to the web pages of the Department of Management in Healthcare at the TU Berlin.

For general information on the various doctoral opportunities at the Charité, please visit the website of the Promotion Office .

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Doctorates in Public Health

A doctorate is a research degree. It demonstrates a person's ability to do original, indepenent, scientific research. A doctorate is a qualification for leadership positions in academia or research.

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Degree Requirements for different Doctorates

The BSPH partner institutions offer a variety of options for doctorates in the field of public health. Each program has a unique focus. Details are stipulated in the respective doctoral program regulations.

Doctoral regulations at Charité and Technische Universität Berlin:

• Dr. Public Health The Dr. Public Health as per doctoral regulations of the TU is open for a wide array of research topics from the public health and global health fields. 
• Dr. rer. medic The Dr. rer. medic. as per the doctoral regulations of the Charité is particularly suitable for research with allied health professions. Main topics include: health promotion and prevention, social determinants of health, social diversity, health services research and the scientifically sound further development of interprofessional cooperation in health care.
• PhD in Health Data Sciences The PhD in Health Data Sciences at Charité offers biostatistics, epidemiology, meta-research and population health science as well as special synergies with innovative developments in public health such as eHealth, digital medicine and medical informatics.
• PhD in Global Health PhD in Global Health at Charité takes a transnational look at health in the Global South and Global North, as well as governance, health policy and the role of climate and environment as the natural basis of health under the framework of the health-related Sustainable Development Goals (SDGs).

Health Data Sciences

Upon successful completion of the program, students will be awarded the academic degree of "Doctor of Philosophy" (PhD).

For more information about the eligibility criteria and admission procedure of the HDS PhD Program as well as the DAAD GSSP scholarships, please visit the program website.  

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Medical Faculty Heidelberg Medical Informatics

Since 1972, within the context of a collaboration between Heidelberg University and Heilbronn University of Applied Sciences, the faculty of the Medical Informatics academic programme has very successfully been educating Medical Informatics Specialists. In international rankings, this academic programme is rated extremely highly.

The provision of efficient and affordable medical care, tailored to the individual patient’s needs, poses an ever greater challenge to our society. State-of-the-art information technologies are therefore indispensable for meeting the challenges of the rapid advances in the medical profession and for driving technical and organisational innovations in the healthcare sector. At the boundaries between medicine, computer science and society, a number of very diverse, exciting, and highly-responsible job tasks have arisen, and along with them, an urgent demand for well-trained and qualified specialists. 

The interdisciplinary field of Medical Informatics is highly diversified, including methodical developments and software engineering for diagnosis and therapy along with simulation and modelling for increasingly individual medical treatment and the development of new procedures in the fields of E-Health and Telemedicine. The planning and assessment of clinical studies is of growing significance and has now become one of the core topics, along with data management and the assessment of new supply strategies and communication technologies in the health care sector.

Special Features and Characteristics

In both research and teaching, these degree programmes involve collaboration with international corporations and other universities. This collaboration guarantees that instruction is linked to current and, in particular, interdisciplinary research. Students who wish to pursue a portion of their studies abroad may select from a number of partner universities, including: 

• France: Université Claude Bernard and Université Savoie Mont Blanc  
• Great Britain: Northumbria University, Newcastle  
• Netherlands: University of Amsterdam  
• USA: University of Washington, Seattle and University of Minnesota, USA 
• Chile: Universidad de Chile  

Students pursuing Medical Informatics degree programmes are enrolled at Heidelberg University and Heilbronn University of Applied Sciences, thus benefitting from the both the practical orientation typical for a university of applied sciences as well as the quality of a university education. Located in attractive surroundings on the Neckar River, both universities offer a broad range of cultural, athletic, and leisure activities.

• Institute of Medical Informatics, University Hospital Heidelberg
• Heilbronn University of Applied Sciences (DE)

Research focuses at Heidelberg University include: 

• Medical image processing and pattern recognition in medicine: Development of systems for computer-assisted diagnosis, monitoring of at-risk patients, and support in planning and implementing therapeutic interventions.  
• Patient-oriented decision support: development of methods and tools for patient-oriented information management and individualisation of medical decisions for doctors and patients.  
• IT solutions for medical research: Innovative IT solutions and information management for the processing and integration of scientific data in medical practice. 

Occupational Areas

Medical informatics specialists enjoy excellent career prospects in industry and healthcare as well as with software companies: 

• Software development, database applications, IT services, information management 
• Medical device development  
• Research and development 

The Medical Informatics degree programmes at Heidelberg University and Heilbronn University of Applied Science provide an in-depth education in Informatics, additionally qualifying students for jobs in fields outside medicine.

Degree variants

Bachelor 100%

Master, consecutive

The degree programme in Medical Informatics run by Heidelberg and Heilbronn universities, has been the ideal preparation for my transition into work. Working closely alongside medical research and care, I develop innovative applications which support patients’ recovery.

Reto Wettstein, Graduate Medical Informatics, Master, Digital Health Engineer at Heidelberg University Hospital

Further Interesting Subjects

Applied Computer Science

Biomedical Engineering

Interprofessional Health Care

Medical Biometry/Biostatistics

Medicine (study location Heidelberg)

Medicine (study location Mannheim)

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GERMANY: 7 Fully Funded PhD Positions in Data Science & Health

Do you want to bring artificial intelligence (AI) and data science to the forefront of health research? The Karlsruhe Institute of Technology is a top-ranked computer science university and Helmholtz research center. The German Cancer Research Center is the largest biomedical research institution in Germany with leading research in health data sciences. The Heidelberg University is the oldest university in Germany with a leading university clinic and excellent track record in scientific computing. These three top institutions joined to tackle this thrilling area by providing a unique doctoral program.

Apply if you can see the potential of techniques like deep learning in the health sector, and if you feel ready for shaping the future of our well-being. We offer projects in a collaborative research environment across discipline borders, focusing on topics in the following data science areas:

• Imaging & Diagnostics

• Surgery & Intervention 4.0

• Models for Personalized Medicine

Requirements:

We are looking for excellent graduates holding a master's degree, received by July 2022 at the latest, in computer science, mathematics, engineering, physics or related quantitative sciences (e.g. bioinformatics or medical informatics).

For a description of the application procedure and to fill in the essential HIDSS4Health application forms please visit https://www.hidss4health.de/#apply prior to submitting your application.

Cutting-edge research and working with top-experts in data science, AI, health and medicine

Inspiring work environment in an interdisciplinary setting

Integrated structured training curriculum of scientific and professional skills taught in English

Financial support for attending conferences and research collaborations, including a funded 4 months visit at a leading international or national research institution or university

A contract for a fully-funded position with competitive salary according to the applicable regulations of the participating institutions (e.g. German E13 TVöD or TV-L) at one of the three HIDSS4Health research institutions

Possible Start Date: Successful candidates will start their scientific work between May and September 2022.

Duration: The position is limited to 3 years with the possibility of prolongation. ​​

Application Deadline: 6 February 2022

Prof. Dr. Klaus Maier-Hein

Phone +49 (0)6221/42-2354

We ask for your understanding that we do not accept applications submitted via email. We apologize for any inconvenience this may cause.

To apply for a position please visit https://www.hidss4health.de/#apply to fill in the required application documents which need to be uploaded with your application.

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The latest techniques and intelligent methods for computer-aided information processing in medicine are the focus of this Bachelor's and Master's programme.

The main focus of the studies is on the following areas:

eHealth – Information Systems in the Healthcare Sector

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Bioinformatics

Computerised collection, processing and application of patient data are playing an ever-greater role for their care in hospitals and doctors’ offices, for managing the system and for clinical research. In our eHealth programme, you will learn how to process patient data efficiently in information systems and to systematically and securely combine these from diverse medical facilities into electronic patient files.

Medical Data Science and Artificial Intelligence

In this new focus you will learn about the latest methods for the evaluation, analysis and interpretation of medical data. Methods of machine learning and artificial intelligence enable an increasingly automated evaluation of complex patient data. Of particular interest here are neural networks and deep learning methods, which open up new possibilities for supporting medical diagnostics and therapy.

Medical Imaging and Signal Processing

In the Medical Imaging and Signal Processing programme, we teach you practical techniques for medical imaging and the latest computer analysis methods and visualisation of medical images and biosignals – which already enable medical practitioners to provide better treatments of patients or will do so in the future.

In our Bioinformatics programme, you will apply informatics methods to biological, especially genetic data, which are becoming increasingly important in advanced medicine.

You will be introduced to cellular biology, genetics and information processing techniques. These are of particular importance for consolidating your knowledge by choosing from among the compulsory courses in bioinformatics.

Job Prospects

For years, the demand has been high for medical informatics graduates.

In view of the growing significance of IT in modern medicine, one expects the demand to keep rising for highly-qualified IT professionals in the healthcare sector and medical engineering.

Medical Informatics Programme

The courses of both the bachelor and the master degree programmes are generally taught in German. In particular, applicants must have a good command of German. Please consult the German pages on the programmes for details.  

Courses Taught in English

Although the majority of the courses in the degree programmes are taught in German, there are a number of courses taught in English that are suitable for exchange students.

German programmes pages

Visiting as an exchange student

Degree Programmes

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•  > Doctoral Student (Ph.D.) in Digital Healt...

Doctoral Student (Ph.D.) in Digital Health: Machine Learning in Medical Care

May 2021 – april 2024.

We are looking for a highly motivated computer science Master’s graduate to fill the project-funded open position on the development and application of machine learning methods in medical care.

Please submit your application documents via email to Bert.Arnrich(at)hpi.de

CASSANDRA – Clinical ASSist AND aleRt Algorithms in visceral surgery

Among the 7.1 million surgical procedures performed annually in Germany, approximately 110,000 operations are related to the four major abdominal organ systems: liver, pancreas, upper gastrointestinal tract (esophagus and stomach) and intestine (small bowl and colon). These rather complex operations are associated with high rates of postoperative complications such as serious bleeding, acute kidney failure, intraabdominal infections and sepsis. In fact, at least one out of four surgical patients experiences at least one severe complication after major abdominal surgery with mortality rates being subsequently as high as 12% according to recent studies. Of particular note, these complications often occur multiple days after surgery - hence, when the patient has already been transferred from an intensive care unit (ICU) to a regular ward with reduced monitoring capacities only. However, early detection of patient deterioration is of key importance to prevent beginning complications from aggravating and finally becoming life-threatening. In septic patients, for instance, every hour of delayed antibiotic therapy induction increases patient mortality by 2%. 

Given the crucial need to improve patient monitoring after surgery, the C linical A ssist AND A lert A lgorithm ( CASSANDRA )-Project aims at developing and evaluating the use of machine learning (ML) algorithms in detecting and predicting postoperative intra-abdominal infections and other complication entities.  The computational challenge in this field emerges from combining static preoperative risk parameters (eg. patient age, medical history, etc.) and static intraoperative data (e.g. duration, blood loss, etc.) with dynamic real time parameters on the ICU as well as on regular wards – the latter using a telemetric continuous vital parameter monitoring device. Taken together, the results may pave the way for an autonomous real-time monitoring system on surgical wards in the long term. The CASSANDRA -project will be conducted in close collaboration with the Surgical Department of the Charité - Universitätsmedizin Berlin and is funded by the Innovation Fonds of the Federal Joint Committee (Gemeinsamer Bundesausschuss G-BA) from May 2021 until April 2024.

Responsibilities

• Support with the setup of a wireless network on a normal ward in order to collect patient vital signs from wearables in real-time.
• Create a pipeline for automatic signal processing.
• Build automatic signal quality checks.
• Clean and filter the signals.
• Extract condensed information from continuous signals.
• Investigate different clinical endpoints like ‘occurrence of a post-surgical complication’ or ‘patient death’.
• Investigate model performance for different subsets of data representing different times during the inpatient stay.

Qualifications

• Master’s degree in computer/data science
• Experience in data mining, computational statistics and machine learning
• Excellent skills in high-level programming languages
• Self-reliance, goal-oriented creativity, dedication, team spirit
• Excellent English language skills

About the Hasso Plattner Institute 

The Hasso Plattner Institute (HPI) for Digital Engineering gGmbH is an institute for teaching and research founded by Hasso Plattner in 1998 as a unique public-private partnership, partially funded by the Hasso Plattner Foundation. The HPI focusses on the design, construction, maintenance and analysis of large-scale IT systems. In recent years, the HPI has been expanding towards new areas in information technology, among others digital heath.

Since 2018, the new research group Digital Health – Connected Healthcare addresses the collection and analysis of health-related data from daily life and in a clinical context. The interdisciplinary team led by Prof. Dr.-Ing. Bert Arnrich includes computer scientists and data scientists working on projects that address the whole pipeline from data collection, data preparation and analysis through statistical methods and machine learning models, up until the presentation of relevant information to clinical practitioners.

About the project partner Charité 

The Surgical Clinic, Campus Charité Mitte|Campus Virchow Klinikum of the Charité - Universitätsmedizin Berlin is one of the largest surgical departments in Europe with over 5000 cases annually. Conducting more than 170 pancreatic, 350 liver, 500 intestinal and 170 esophageal and gastric surgical procedures per year, it is one of only a few surgical single centres providing a number of operations high enough for the development and evaluation of various machine learning algorithms. The challenging process of systematic data collection and digital storage throughout inpatient stays has already been introduced and continuously been optimized at the Campus Virchow Klinikum as part of the Enhanced Recovery After Surgery (ERAS ©)-program that works an holistic perioperative documentation concept.

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Higher Education Compass

Biomedical data science part time degree programmes for professionals, full time, master of science.

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Infection Biology, Imaging, Data Science, Data Analysis, Big Data

In the interdisciplinary and practice-oriented Master's degree course in Biomedical Data Science, the scientific thinking, working and procedural methods from a completed Bachelor's degree course in biosciences or medical degree are expanded and strengthened. At the interface of life sciences and medicine, the focus is on the generation and targeted handling of large, heterogeneous and complex amounts of data as well as the development of IT solutions, e.g. for disease prevention, precise diagnoses, treatment and therapy decisions as well as for the evaluation of extensive research data.

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Bachelor's degree in biological sciences Degree in human medicine with licence to practise Application from 01.06. to 15.07 of each year at https://campus.mh-hannover.de

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• 07.10.2024 - 21.03.2025
• 08.04.2024 - 27.09.2024

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Study Bioinformatics in Germany: 9 Universities with 10 English Degree Programs

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The field of Bioinformatics merges biology, computer science, and statistics to analyze and interpret complex biological data. This involves applying computational algorithms and statistical methods to understand structures, functions, and interactions of biological entities from genes to ecosystems. In our era of big data and genomic revolution, this includes working extensively with high-throughput genomic data, protein structures, and bioinformatic databases, amongst other resources. This interdisciplinary field is rapidly advancing, driving discoveries in numerous areas such as personalized medicine, ecology, and evolutionary biology. Embark on your educational journey in this vital and innovative discipline with a comprehensive program from a German university!

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3 english degree programs for bioinformatics in germany.

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Ehealth and communication.

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Molecular Medicine

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Deggendorf Institute of Technology Deggendorf

Life science informatics.

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Molecular biotechnology (mbt).

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Computational biology and bioinformatics.

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Home News CCTSI Appoints New Leader in Health Informatics back to News

CCTSI Appoints New Leader in Health Informatics

minute read

Jayashree Kalpathy-Cramer, PhD, came to the University of Colorado Anschutz Medical Campus in June 2022 to launch the new Division of Artificial Medical Intelligence in Ophthalmology at the University of Colorado School of Medicine. In her role, Kalpathy-Cramer translates novel artificial intelligence (AI) methods into effective patient care practices at the Sue Anschutz-Rodgers Eye Center.

Just two years later, Kalpathy-Cramer has joined the leadership of the Colorado Clinical and Translational Sciences Institute (CCTSI) as director of Health Informatics.

“Translational Informatics is the study and application of existing data to bridge new ways to improve diagnosis, prognosis and treatment of disease,” said CCTSI Director Ron Sokol, MD. “We are thrilled to welcome Dr. Kalpathy-Cramer to the CCTSI. With her deep experience in engineering, AI, and bioinformatics, she will help facilitate and lead groundbreaking research across our institute.”

“I am truly honored to be appointed to the role of director of Health Informatics at the CCTSI. This role presents an incredible opportunity to continue to foster collaboration and innovation and drive forward our mission of enhancing translational research and education,” said Kalpathy-Cramer. “It is an exciting time for our institution as we leverage informatics and AI to harness the power of data to advance scientific discoveries and translate them into meaningful solutions that impact patient care."

Kalpathy-Cramer has already accomplished a great deal in the two years since she has been on the Anschutz Medical Campus. The Michael J. Fox Foundation awarded her a grant to research the use of AI to identify biomarkers of Parkinson’s disease, a progressive disorder that affects the nervous system and causes uncontrollable movements, such as shaking, throughout the body.

She recently won an Anschutz Accelerator Award for her project “Oculomics as a Biomarker for Comprehensive and Non-Invasive Patient Health Assessment.” Oculomics is the study of the association between ophthalmic biomarkers (changes or abnormalities in the eye) and systemic health or disease states. She and her multidisciplinary team aim to bring AI-assisted ophthalmic imaging outside of ophthalmology to improve patient health and clinical outcomes, meet quality metrics and reduce health system costs. This work will further advance the field of oculomics; and, if successful, it could become an inexpensive and mainstream tool to assess patient health.

Before she came to Colorado, Dr. Kalpathy-Cramer directed the Quantitative Translational Imaging in Medicine (QTIM) lab and the Center for Machine Learning at the Athinoula A. Martinos Center for Biomedical Imaging, and was an associate professor of radiology at Harvard Medical School.

“Even during my relatively brief time at CU, I have seen what a phenomenal resource the CCTSI is,” Kalpathy-Cramer said. “I look forward to learning more from the CCTSI community about the opportunities that informatics has for moving their research forward and how the informatics core can best support that.”

“In terms of her work with us at the CCTSI, she is jumping in feet first! Already, she is helping to develop the agenda of the CCTSI’s upcoming CU-CSU Summit,” said Sokol. The topic this year is Research Innovations in Health AI. For more information on how to register or submit an abstract to present a poster, click here .

Topics: Research , Kudos , Artificial Intelligence (AI)

Jayashree Kalpathy-Cramer, PhD

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Study: Researchers use big data to establish long COVID subtypes based on more than 250,000 VA patients

Data-driven long COVID definition will help support public health initiatives while providing clinicians with a more nuanced basis for screening and diagnosis

By Ellen Goldbaum

Release Date: June 22, 2024

BUFFALO, N.Y. — The announcement earlier this month from the National Academies of Science, Engineering and Medicine of a consensus definition of long COVID mentioned that it was not the final word on this condition but that the definition would be revised as new findings are published.

Earlier this year, researchers at the University at Buffalo and the Department of Veterans Affairs who were using big data to work on a data-driven long COVID definition were invited to report their findings in testimony before the National Academies.

In April they published those findings in JMIR Public Health Surveillance based on more than 250,000 patients in the Veterans Health Administration who had tested positive for COVID.

Finding different subtypes

“Because we had such large numbers of patients at the VA, it was a wonderful place to do this study,” says Peter L. Elkin, MD, corresponding author and chair of the Department of Biomedical Informatics in the Jacobs School of Medicine and Biomedical Sciences at UB. “We looked at the full electronic health records of patients so that we could tease apart all the different symptoms of this complex disease to find all the different subtypes that exist.”

One of the goals is to help clinicians better recognize cases of long COVID. “The idea is to make more clinicians aware of who has long COVID and who is maybe not yet out of the woods from long COVID,” he explains. “Now that we have a definition, you can tell who in your specialty has long COVID and who doesn’t.”

The findings could help researchers develop a more scientific approach to finding out how COVID infection causes the specific conditions seen in long COVID.

The study was done using the electronic health records of more than 2.3 million patients who were seen at a VA health facility between Jan. 1, 2020, and Aug. 18, 2022. There were 367,148 patients who tested positive for COVID-19 at a VA facility; of those, 268,320 were considered to have long COVID if they had a novel diagnosis between one and seven months following a positive COVID-19 test.

Based on the symptoms experienced by patients with long COVID, the researchers assigned a total of 324 ICD (International Classification of Disease) codes. They identified 180 clinical scenarios and 17 clinical subtypes that were upregulated in people who had long COVID.

Highest case counts in cardiology

The highest long COVID case counts were in cardiology, with diagnoses including low blood pressure, heart failure, arrythmias and atrial fibrillation, followed by neurology (symptoms included low back pain, severe muscle weakness and cognitive impairment), ophthalmology and pulmonology.

Among the most commonly cited symptoms were fatigue and acute respiratory distress. Respiratory issues are among the most common in long COVID, including chronic cough, respiratory failure and dependence on supplemental oxygen. Cognitive difficulties, including brain fog, were also frequently cited.

Factors that put patients at higher risk for developing long COVID included older age, other health conditions prior to becoming infected, a more severe case of COVID and low oxygen saturation during COVID. Patients who had not received a COVID-19 vaccine were 1.3 times more likely to develop long COVID.

The study provides definitions of each of the long COVID subtypes and odds ratios defining the risk for each of them.

“These data will allow us to better identify patients with long COVID and it can also help support public health research and policy initiatives going forward,” Elkin says.

The authors note that a limitation of the study was that the study population was 84% male.

Co-authors with Elkin are Skyler Resendez, PhD, a postdoctoral fellow; Hugo Sebastian Ruiz Ayala; and Prahalad Rangan, PhD, all in the Department of Biomedical Informatics in the Jacobs School; and Steven H. Brown, MD; Jonathan Nebeker, MD; and Diana Montella, MD, of the Office of Health Informatics of the Department of Veterans Affairs.

The work was supported by the National Library of Medicine, the National Institute on Alcohol Abuse and Alcoholism, and the National Center for Advancing Translational Science, all of the National Institutes of Health, as well as the Department of Veterans Affairs. 

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Pitt’s online health informatics ms program earned a top 5 national ranking.

The online master’s in health informatics program at the University of Pittsburgh has been ranked No. 4 in the nation for 2024 by AnalyticsDegrees.org.

The School of Health and Rehabilitation Sciences (SHRS) program aims to position graduates to leverage technology to enhance health care delivery. Students are equipped with skills to standardize data, improve patient lives, spot trends and create efficiency in health care processes.

“It is great that our MS in health informatics program has been recognized as one of the top programs in health data science in the country,” said Bambang Parmanto, chair of the Department of Health Information Management at SHRS. “There are multiple standout features of our program. We have a well-designed curriculum, strong faculty and exceptional support for students, including faculty availability to support students and dedicated staff for engaging students.”

This ranking underscores the robust curriculum, esteemed faculty and exceptional student support, according to program director Leming Zhou, associate professor of health informatics.

Health informatics is a rapidly growing field, driven by the integration of technology in health care. With U.S. health care spending at $4.5 trillion annually and employment in medical and health services management expected to grow by 28% by 2032, the demand for skilled professionals in this area is high. The median annual salary for these roles is $104,830.

Delivered through the Department of Health Information Management, Pitt’s program offers a customizable curriculum designed to fit students’ schedules, whether they attend full-time or part-time. The program’s weekly synchronous sessions for both online and on-campus students contribute to its high quality, Zhou added.

Faculty are actively engaged in funded research and incorporate the latest advances, such as AI, into the curriculum. The program also features a peer mentoring initiative that connects successful alumni with current students, along with internship and capstone components that allow students to work on real industry projects using cutting-edge technologies.

“We constantly ask for feedback from our students and alumni,” Parmanto said. “We aim to grow our programs further and attract more international students.”

AnalyticsDegrees.org evaluates nearly 600 colleges and universities offering more than 2,000 analytics degree programs. The platform’s rankings focus on curriculum relevance, program reputation, and student success metrics such as graduation rates, post-graduation earnings and external awards.

Applications are still open to begin in the upcoming fall semester. The deadline is July 29.

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