The dominant demographic trend of the 21st century is population aging. Virtually all countries of the world are getting older, creating pressure to transform the ways in which societal and economic structures as well as individual life courses are arranged. Understanding these challenges requires deep demographic knowledge combined with interdisciplinary expertise in epidemiology and population health, and proficiency with econometric, statistical, data science and computational methods.
The International Max Planck Research School for Population, Health and Data Science (IMPRS-PHDS) is a new and unique three-year doctoral program that merges demography, epidemiology and data science. The PHDS school equips doctoral students not only with advanced knowledge of the theory and methods of demography and epidemiology (broadly defined as ‘population health’), but also with strong technical skills in statistics, mathematical modeling, and computational and data management methods (broadly referred to as ‘data science’).
IMPRS-PHDS is hosted at the Max Planck Institute for Demographic Research (MPIDR; www.demogr.mpg.de) in Rostock, Germany. Founded in 2019, the school receives core support from the Max Planck Society, MPIDR, University of Rostock, and ten affiliated institutions. It does not charge fees, and makes available about 15 three-year PhD positions every year. The school’s curriculum is targeted to pre-doctoral students entering the School with a Master’s or equivalent degree and offers
IMPRS-PHDS is run by two core partners and ten affiliated institutions.
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- Health, work ability, and labour force participation:
Studies on effects of hazardous working conditions and individual lifestyle factors on work ability and health, and subsequent consequences for work (i.e. productivity, sickness absence, permanent disability, and early retirement). Studies on effects of health on labour force participation in the general population and among workers with chronic diseases. Methodology development in assessment of long-term consequences of ill health (lifecourse perspective; working life expect and c) in measurement of productivity loss at work.
- Health impact assessment: Studies on effects on primary preventive interventions on population health (Rotterdam) and studies on the costs and effects of interventions on population health and life expectancy.
- Reintegration towards paid employment: Experimental and observational studies on effects of reïntegration programmes combining health interventions and labour market activities.
I am working at the intersection between public health and demography. My research interest concentrate on health expectancy, disability and mortality. My work focusses on describing and explaining socioeconomic and gender differences, and variations herein between countries. I am particularly interested in the contribution of diseases and risk factors to variations in disability, mortality and health expectancy. My work also focusses on health impact assessment and projecting life and health expectancy. I am interested in developing, using and disseminating tools that help to understand better trends and disparities in disability, mortality and health expectancy and to assess the impact of risk factors and policy interventions on health and health disparities.
My research interests concentrate on understanding the mechanisms and factors involved in the explanation of socioeconomic inequalities in health and health related behaviours, both at the individual and neighbourhood level. I am intrigued by understanding the development of socioeconomic inequalities in health in early childhood and in old ages, at the individual and neighbourhood level. In my research, the role of economic, physical, social, and cultural factors for health and health inequalities are important. As a result of the interest in environmental factors, a related interest concerns healthy ageing among cities in Europe. In addition to understanding the background of health inequalities, I am interested in understanding how to reduce health inequalities though policies, (natural) experiments and behavioural interventions. In all work, state-of-the art social epidemiological methods are preferably used.
I am an epidemiologist, demographer, and applied statistician with a strong interest in methods from counterfactual causal inference. My current research focuses on the g-formula, a flexible method for modeling complex dynamic longitudinal relationships. Substantively, I am very interested in the life-course, and with this method I am investigating the relationship between health, fertility, partnership and employment across the life course. Methodologically, I am combining the g-formula with multilevel modelling techniques and with techniques accounting for unmeasured confounding. Furthermore, I have developed expertise in the topic of age-period-cohort analysis and continue to have an interest in APC methods and their application. More generally, I am interested in population health, in particular cardiovascular & mental health, drug utilization and drug effectiveness. I aim to do more work in the field of fertility and families as well.
I have deep expertise in data analysis and its broad application in the social sciences. My particular research interests are in the fields of demographic forecasting, method validation, formal and statistical demography, and complex data visualization. I typically combine cutting-edge methods of statistical analysis, computational science, and statistical demography to analyze population processes and their driving forces from different angles. The methods I develop and the human demographic contexts in which I apply them vary widely, covering, e.g., mortality, population health, and fertility.
- Life course research with a focus on labor market outcomes and modeling of life course trajectories
- Inequality measurement with a focus on income and wealth, and an interest in health inequalities
- Causal inference with a special interest in identification and partial identification
- Other topics I am interest in or I have worked on include: survey statistics, in particular imputation and variance estimation; household economics; social policy and population aging; kinship; demographic forecasting, in particular stochastic forecasting
Health economics - Aging and retirement; work, health and health behavior; determinants of healthcare utilization; use of preventive care and screening; neighborhood determinants of health; fertility; Applied econometrics – Causal inference on observational data; regression discontinuity design; Bayesian econometrics; spatial econometrics
Statistical Demography; statistical modelling in demographic applications; event history analysis, including complex sampling patterns; recovering latent information from observed data; multi-state models; micro-simulation; smoothing techniques and estimation under penalty restrictions.
Population health with particular focus on behavioral factors as determinants of trends and differentials in health and mortality; causes and consequences of low and late fertility; the demography of labor markets; multistate demography; demographic forecasting.
Gender differences in health and survival; life course and health; migrant health; cross-national comparison studies of health; dynamic of healthcare use at older ages; biological markers of health; register-based research
My research centers on the intersection of mathematical demographic approaches, population health, and mortality. My mathematical interests divide roughly into three application areas: 1) extensions of stable and stationary population theory, and its applications to the indirect estimation of age-at-onset patterns for difficult-to-detect transitions to unhealthy states, such as pre-clinical dementia; 2) Developing a rigorous framework of high-order Lexis time relationships and data operations, with applications in health pattern detection, as well as the measurement, modeling, and prediction of demographic phenomena; 3) Developing decomposition techniques that can be used to measure and understand changes and inequalities in population health attributable to i) mortality, and the onset and recovery processes, and ii) the duration composition of episodic health states. These methods can be used to give fresh perspectives on classic questions of morbidity expansion or compression, as well as even more macro concerns, such as the future potential of the longevity revolution. I also develop R packages and data visualization techniques for all things demography-related.
Methods and empirical research on population and health; measurement and analysis of inter-individual and inter-group disparities in health; methods for decomposition in demography; convergence and divergence in demographic patterns across populations; biomarker studies on health and aging; mortality and health in Russia and Eastern Europe; study on health and social change; macro- and micro-level studies on alcohol and other determinants of premature death among adults.
Variation in ages at death (lifespan inequality) and life expectancy; Socioeconomic inequalities in health and mortality; The impact of healthy/unhealthy behavior on health and mortality; Mortality forecasting; Decomposition analysis and formal demography.
Zagheni uses mathematical, statistical and computationally-intensive approaches to study the causes and consequences of population dynamics. Motivated by the ambition to improve people's lives through the scientific study of our societies, he is strengthening a portfolio that leverages interdisciplinary approaches to monitor demographic change, to explain population processes, and to predict future demographic outcomes. More specifically, his research addresses three main inter-related topics: (i) combining large social media data with traditional sources to track and understand migrations; (ii) evaluating the consequences of population aging on intergenerational transfers; (iii) modeling the relationships between population dynamics, the environment and infectious diseases. A common thread across his substantive interests is a consistent drive to develop methods and to analyze data in creative ways that further advance our understanding of social phenomena. Zagheni has been the Director of Training at the University of Washington Center for Studies in Demography and Ecology (CSDE)
Use of health claims data for assessment of quality of care and outcome evaluation in routine health care; Clinical studies in primary care; Pharmakoepidemiology; Systematic reviews and metaanalysis; Research in medical education
Epidemiological studies with focus on cardiovascular diseases in the general population and clinical cohorts; Clinical cardiovascular studies with focus on heart failure and common cardiovascular diseases; Subclinical cardiovascular changes; Individualized therapy of cardiovascular diseases; Prevention of cardiovascular diseases; E-cardiology
Thyroid epidemiology; Reference interval calculation; Causal inference; Non-linear modelling
Bioinformatics; Machine learning and data mining approaches in biomedical applications; Biostatistics; Mathematical Modeling of biological and epidemiological processes
social epidemiology, behavioral epidemiology, psychiatric epidemiology, population based intervention research, implementation research, e-health, behavior modification, tobacco smoking, alcohol use, substance use, health behavior change
quality management in cohort studies, data quality; research consequences, focus incidental findings in MRI; statistical survey methods and selection bias; epidemiologic and genetic risk factors for subclinical diseases; primary care research; musculoskeletal diseases; routine data / data linkage; evaluation of clinical interventions
The main aim of the whole work is the development of brief intervention strategies aiming to reduce the proportions of individuals with cardiovascular risk factors in the general population. In the past years we finished several studies according to efficacy of motivational approaches, i. e. interventions by which we aimed to increase the motivation to stop smoking or to reduce the second hand smoke exposure in children ≤ 4 years. Further, I`m interested in implementation of effective measures supporting individuals to improve their lifestyle skills in primary medical care. In 2014 we started the development and test of a brief intervention, aiming to reduce physical inactivity in leisure time. Actually, we are interested to clarify the gap between results of physical activity measurement via self-report and via wearable devices (i. e. accelerometer).
Henry Völzke is professor for clinical-epidemiological research and head of the Department of SHIP/ Clinical-Epidemiological Research at the University Medicine Greifswald with basic training as certificated internist. He has been involved in research projects funded by European Union, the German Research Foundation and numerous other public and private funding bodies and is member of several large national and international research consortia. His broad research interests cover common, population-relevant diseases including thyroid and other endocrine disorders, cardiovascular, metabolic and gastrointestinal diseases. In PubMed he is listed with more than 750 publications in international peer reviewed journals (h-factor 101). He is PI of the Studies of Health in Pomerania and Scientific Director of the Northeast German part of the German National Cohort as well as Co-PI of the GANI_MED project and the Greifswald site of the German Centre for Cardiovascular Research. He coordinates the H2020 funded EUthyroid consortium. Henry Völzke is past president of the German Society for Epidemiology (DGEpi) e.V and the German representative in the IGN – Iodine Global Network.
Disparities in health and mortality across educational groups are striking and pervasive, and are considered one of the most compelling and well established facts in social science research. It is commonly assumed that a large part of the association between education and health derives from the causal effect of education on health outcomes. My main research interest is to disentangle this causal effect of education on health and mortality from the selection effects. An important aspect of my work is that I not only try to account for selective choice but also for dynamic selection, inherent to outcomes that evolve over time, such as survival and health status. For all these analysis I use state of the art event-history methods, or development new methodology. Another research interest is to measure the impact of early life circumstance and experiences on later life (health) outcomes, accounting for (dynamic) selection and selective survival. I have also interest in analyzing the return migration behaviour of recent migrants, investigating the influence of labour market and health changes. Again with a focus on (dynamic) selection. Thus allowing for interdependence between labour market and health changes and the decision to migrate.
Mortality, health, ageing, time trends, mortality forecasting, health determinants, lifestyle, smoking, alcohol, obesity, sex differences, geographical differences, causes of death
Family life course, Residential relocations, Partnership formation and dissolution, Leaving the parental home, The transition to homeownership, Health and well-being from a life-course perspective
Population projections, Regional demography, Economic-demographic modelling, Demography of firms and enterprises, Aging and mortality, Spatial interaction models, Longitudinal data analysis
social and economic determinants for health and longevity; policy interventions and their effects on health and mortality; intergenerational transfers, health and mortality
My current research program focuses on three main areas, 1) psychosocial factors in health and well-being, 2) theory-based behavior change interventions, and 3) psychosocial aspects in genomic research. In research area (1) we are investigating how different psychosocial factors are prospectively related to health and wellbeing. Specifically, how general and behavior-specific psychosocial factors predict health and heath behavior outcomes. Related to theory based intervention studies (2), we are running school based intervention and technology based intervention studies. In research area (3), key questions include what the psychological consequences of genetic testing among families with heritable diseases, and in ongoing project how different genetic information should passed at the population level.
My research focuses on the social determinants of health. In particular, I have been investigating employee mental health and socioeconomic inequalities of health. My other current interests regard the investigation of migrant health; as well as digitalisation and social inclusion of migrants. My research involves the application of social epidemiological methods and administrative record linkage, large-scale prospective survey designs, and RCTs.
I am one of the WP leaders (Pis) in Towards socially inclusive digital society: transforming service culture / Consortium: DigiIn; PI of the Effectiveness of internet-delivered cognitive behaviour therapy (iCBT) in reducing sickness absence among young employees with depressive symptoms (DAQI); and one of the Co-Is of the Administrative Data Research Centre in Northern Ireland (ADRC-NI), which is a part of the UK-wide ESRC-funded Administrative Data Research Network.
A substantial part of Pekka Martikainen’s research interests are associated with changes and causes of socioeconomic differences in cause-specific mortality. However, he is also interested in other population sub-group differences in health; these relate in particular to the effects of marital status and widowhood on health, unemployment and mortality, and the effects of household and family characteristics on health. He is also involved in cross-national comparisons of health inequalities. These have been partly carried out under the auspices of various EU-funded consortiums, partly in collaboration with the Helsinki Health Study and the Whitehall II Study. More recent interests are associated with the consequences of population ageing, formal institutional long-term care and care use before death. His most recent project tries to understand the accumulation of poor health and social disadvantage in households and across generations from a life-course perspective. Pekka Martikainen is responsible for the development and maintenance of longitudinal register based data that has been used for the study of various demographic phenomena.
My central research topics cover socioeconomic and global health inequalities, physical and mental development of children and risk factors of metabolic diseases. I have been especially interested in biosocial interactions and international comparisons. Applying quantitative genetic models to international data makes possible, for example, to analyze how social macro-environment can modify the effects of genetic and environmental factors on health and health behavior. Currently, I am the principle investigator of the CODATwins project, which has combined twin data from 24 countries and is currently the largest twin dataset in the world.
- Gender inequality and ist demographic implications: health and mortality implications of son preference in infancy and childhood, prenatal sex selection and sex ratio at birth distortions, gender gaps in early and later life health.
- Digital and computational social science: agent-based modeling and microsimulation, nowcasting social development indicators with digital trace data, gender inequalities in internet and mobile phone access, implications of the digital revolution for economic and social development.
- Demographic analysis of marriage and family: assortative mating, marriage squeeze and the implications of educational expansion for marriage and family behaviour.
- Ethnicity and migration: measuring migrant integration and heterogeneity, heterogeneity in social attitudes and demographic norms among migrant communities in Europe.
Demography; Sociology; Life course research; Sociogenomics (combining molecular genetics and sociology); Cross-national comparative research; Non-standard work schedules; Inequality; Event History Analysis; Quantitative Statistical Genetics; Fertility; Family; Assortative Mating
Inequality, Health, Mortality, Family formation, Divorce, Marriage patterns, Social stratification, Twin rates, Family size, Childlessness
Trends and patterns in the health of the elderly population; Cognitive functioning and neurodegenerative disease; Care need and care need projections; Early life factors of late life health and mortality; Health of migrants; Social differences in mortality and health
Analysis of Mortality: Oldest-Old Mortality; Mathematical Demography; Statistical Demography; Mortality Forecasting; Socio-economic differences in mortality
The research interest is in developing methods for multi-level modeling and simulation and their applications. Methodological developments range from the design of formal modeling languages, the development of efficient algorithms, to providing computational support for more effectively conducting entire simulation studies, involving diverse simulation experiments. Current applications focus on ecological, cell biological, and demographic simulation studies.
Urška Demšar’s research area is Spatio-Temporal Visual Analytics with specific focus on visual analytics for computational movement analysis. She is combining analytical and visual techniques and is particularly interested in visual interpretation of results of spatial and spatio-temporal statistical methods. She collaborates with researchers in a number of application areas, including human dynamics, eye tracking research and animal movement.
Jo Mhairi Hale’s research agenda focuses on the association between health and well-being and intersections of race/ethnicity, gender, socioeconomic status, and migration, contextualized by structural factors such as economic recessions and social welfare spending. One key area of interest for Dr. Hale is identifying the social and behavioral risk factors for later-life cognitive impairment and dementia mortality, taking a life-course approach. She has analyzed administrative datasets such as the Center for Disease Control WONDER database, as well as multiple cross-sectional and longitudinal survey datasets, including the National Agricultural Workers Survey, the Health and Retirement Study, and the Survey on Income and Program Participation. She has utilized both qualitative and quantitative methods and has worked with scholars from a range of disciplines, including epidemiology, public health, formal demography, and economics.
Hill Kulu’s substantive research interests lie in the field of family, migration and health studies. Within health studies, Kulu has investigated social and environmental determinants of health and mortality in industrialised countries including mortality differences by migrant status (immigrants versus natives), marital status (married versus non-married) and place of residence (urban versus rural). He is currently supervising two PhD projects on short- and long-term effects of air pollution and temperature on population health and mortality. Kulu’s methodological interests include the development and application of survival analysis and multistate models in health and mortality research including the application of simultaneous equations random effects models to detect and control for the effect of unobserved heterogeneity and selectivity. He has expertise in working on large scale administrative data (e.g. the Office for National Statistics Longitudinal Study) and longitudinal survey data (e.g. the British Household Panel Study; the Understanding Society study).
My research expertise focuses on the interdisciplinary and highly policy relevant area of human migration, and a commitment to research that is of conceptual and practical significance underpins my research philosophy and activities. My research concentrates on how population mobility relates to the functioning of the economy and experiences of work. My endeavours in this area have contributed to new methodological and conceptual ways of thinking about migration, and have generated significant practical impact (impact case study for next REF). I am an Editorial Board member of Population, Space and Place (ranked second in Demography) and am an active participant in academic networks within the social sciences (e.g. I am the University of St Andrews Institutional Representative on the ESRCs Scottish Graduate School of Social Science) and have a strong record of attracting Research Council funding (e.g. part of ESRC Centre for Population Change). Consequently, I have successfully delivered a number of research projects, often involving leading numerous Research Fellows and co-investigators. I am an active contributor to the research strategy of our School via our Research Committee.
Julia is a Senior Research Fellow at the University of St Andrews and at the ESRC Centre for Population Change. Her research focuses on the consequences of changing partnership and family dynamics for individuals’ outcomes across Europe using longitudinal data and advanced longitudinal methods (e.g., (multiprocess and multistate) event history analysis, sequence analysis). More specifically, she has studied the interrelationship between multiple partnership transitions and the transition to motherhood across Europe. She has also extensively studied the consequences of separation and divorce for individuals’ residential mobility and housing in several industrialized countries. Julia has extensive experience of using the British Household Panel Study, the Understanding Society study, and data from the Generation and Gender Surveys.
My research interest cover welfare research, health inequalities and social determinants of health. More specifically, I have worked on topics such as the size and trends of health inequalities in Sweden and internationally; general welfare trends in Sweden (in particular during the crisis in the 1990s); income, relative deprivation and health; the importance of childhood conditions for adult health; Sense of Coherence and its connection to health; and health among older adults. I have also worked a lot with policy issues on the nationally as well as the international level. Among other things I led a Task group for the Review of Social Determinants and the Health Divide in the WHO European Region, and was appointed by the Government to chair the Swedish Commission for Equity in Health.
Common to practically all of my research is the focus on childhood social disadvantage and its implications for people’s present and future health, as well as the ambition to identify the pathways through which such influences operate. In line with this, my more recent research addresses the question of how social inequalities in health are transferred and maintained across family lineages spanning several generations. In a different vein of my research, concentrating on a much narrower time-span, I investigate how different features of the school context shape and modify present-day children’s level of stress and mental well-being. I have a quantitative approach, using statistical techniques such as proportional hazards models, multilevel analysis, and structural equation modelling to test my hypotheses.
Social capital and health in a policy perspective; The theoretical foundations of social capital; Immigrant health; Labour market conditions and health among immigrants; Social support, social networks and health behaviours; Health consequences by bereavement
I am a sociologist and demographer, researching social dynamics at the intersection of gender, globalization, migration, development, and environment. I also teach and publish in the fields of pedagogy and methodology, both related to training of graduate students, particular about research ethics, mixed methods, and qualitative field methods.
Spatiotemporal models, graphical models, multidimensional contingency tables, loglinear models, Bayesian statistics, statistical computing, modeling of complex dynamical phenomena using big data, computational social science
Statistical methods for population health in settings with limited or low quality data; sampling populations that are difficult to include on traditional surveys; using social media or other forms of passively observed data to infer representative population quantities.
Estimating child mortality in a low and medium income country context; hierarchical models for survey data; spatial epidemiology; space-time models for infectious disease data; small area estimation; estimating national and subnational disease burden; ecological inference for non-infectious and infectious disease data; the links between Bayes and frequentist procedures
The PHDS program is characterized by eight components that focus on guaranteeing strong interdisciplinary training in population, health and data science, but also aim to deliver high-quality supervision across more than one institute, give the students extensive networking opportunities, provide the students the opportunity to work at minimum at two leading research institutions, and foster a strong cohort experience despite having the students hosted at several locations.
Candidates interested in joining PHDS are asked to apply to the school with a research proposal and a clear preference for a hosting institution. Each of the partners in the PHDS qualifies as a hosting institution. Upon acceptance, a student gets assigned a primary supervisor from his/her hosting institution and a secondary, informal supervisor from one of the other partner sites. With these arrangements in place, each PHDS student is jointly supervised by faculty from (at least) two partner sites. This immediately gives the students an unusually broad supervising network, facilitating dissertation work for which expertise at one site is not enough.
The academies are held once per year, are attended by all students and their supervisors, and run for three to five days. Each academy consists of five components: research presentations and lectures by eminent scientists who are external to the PHDS network, faculty research presentations and instruction, student presentation of dissertation research with feedback from their peers and faculty, a kick-off event for the incoming cohort, and collegial exchange between faculty and students. The first academy is scheduled for 4-6 November 2019 and will be held at the MPIDR in Rostock.
The MPIDR organizes a core training program for the core students that are based at the core partners MPIDR and University of Rostock. The core training program at the MPIDR is mandatory for the core students and optional for the affiliated students based at the affiliated partner sites. The core training program involves a mix of basic and advanced courses. Three basic courses focus on (i) demographic measures, (ii) population health and (iii) data science and population processes. These basic courses provide an introduction to key themes of PHDS involving practical (computer) exercises and will normally be presented as 10-day intensive courses in November and December. Several advances courses focusing on specialized topics in population, health and data science are offered throughout the entire year.
PHDS partner institutions will open their already existing courses on population, health and/or data science to PHDS students. Students will thereby be offered the opportunity to participate in courses at all partner sites. A list of seminar courses at partner sites will become available in winter 2019/20.
From 2020 onwards, PHDS will offer optional thematic workshops focusing on specialized research topics within the overall theme of the school. A thematic workshop will run for two to three days and will bring together students, faculty as well as external experts working on this particular topic. Students attending thematic workshops are encouraged to present at these workshops.
From 2020 onwards, one graduate workshop will be held per year, always in Rostock. Graduate workshops will bring together the PHDS students. They will present progress reports, research outlines as well as preliminary and advanced dissertation research. Students will receive feedback from their peers and from one or two PHDS faculty.
Each PHDS student is required to complete one three-month stay abroad at one of the partner sites. For most students, this will be the site where the student’s secondary supervisor is based. Students may combine their research stay abroad with attending a course and/or a thematic workshop at the partner site. Thus, PHDS students will be internationally mobile and benefit from exchange with other European and US universities. Affiliated students are encouraged to complete their research stay at one of the core partner sites (i.e., MPIDR or University of Rostock) because most of the PHDS activities take place in Rostock.
TACs are established as a supervisory structure for all PHDS students. A TAC generally consists of a maximum of 4 members, selected by the PhD student in close consultation with his/her primary supervisor and assisted by the Dean. In this way, TACs provide an opportunity for students to expand their professional network in a targeted way that favors their employment opportunities after the doctorate. In most instances, TAC members are recruited from the PHDS teaching faculty. When composing TACs, particular attention is paid to the fact that TAC members are independent of one another. TAC meetings are held at least once a year and are documented.
Involvement in and effort for PHDS varies slightly for core versus affiliated students.
Model schedules A and C show basic participation (only mandatory curriculum elements) while model schedules B and D illustrate intensive participation (mandatory and optional curriculum elements). Note that optional curriculum elements can be arranged individually according to the students’ interests and needs.
11.11.2019 – 15.11.2019
Max Planck Institute for Demographic Research, Rostock, Germany
Course coordinator: Alyson van Raalte
Course Outline (PDF)
18.11.2019 – 29.11.2019
Max Planck Institute for Demographic Research, Rostock, Germany
Course coordinator: Yana Vierboom
Course Outline (PDF)
Fundamentals of Digital and Computational Demography
02.12.2019 – 13.12.2019
Max Planck Institute for Demographic Research, Rostock, Germany
Course coordinator: Emilio Zagheni
Course Outline (PDF)
Application in 2019 was restricted to current doctoral students from the current PHDS partner sites. The first open IMPRS-PHDS Call for Applications will be published in February 2020.
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