One position as Associate Professor is available at the Oslo Centre for Biostatistics and Epidemiology (OCBE), Institute of Basic Medical Sciences (IMB), the Faculty of Medicine, University of Oslo (UiO), Norway.
OCBE wishes to strengthen its capacity in machine learning and is looking for candidates with expertise and experience in statistical theory and methods with focus on machine learning, together with a strong interest in applications to medicine, including basic medical research, clinical medicine, epidemiology and/or public health. The post is with tenure and permanent.
Applicants must show promise to become leading academics. They must document an already solid publication record, some experience in research leadership and teaching, and experience with applying for research funding. Together with your colleagues at OCBE, you will shape research and teaching leadership in this fast-developing discipline.
The Oslo Centre for Biostatistics and Epidemiology (OCBE) is a joint department of the University of Oslo (UiO) and Oslo University Hospital (OUS). OCBE has expanded considerably during the last decade, becoming one of Europe's most active biostatistics and epidemiology groups. Currently, OCBE includes twelve tenured professors and associate professors, fifteen tenured researchers and senior researchers, and many postdoctoral fellows, PhD students and visiting scientists, making up a group of over 70 researchers.
OCBE’s research is internationally recognized, in particular in the areas of time-to-event models and causal inference; epidemiology of lifestyle, chronic diseases and infectious diseases; methods for high-dimensional data and data integration, especially in molecular medicine; mathematical modelling of cancer; probabilistic modelling and Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. OCBE has collaborations with leading biomedical research groups in Norway and internationally. OCBE has acquired major research funding from the Norwegian Research Council, the European Union (including an ERC Advanced Grant), the Nordic Research Council, the Norwegian Cancer Society and several other public and private agencies.
OCBE is responsible for the biostatistics teaching in the professional study programme in Medicine, the Faculty's master programmes and the PhD training. OCBE also provides an extensive statistical advisory service for biomedical and clinical researchers at UiO and OUS - often an exciting source of data and challenges for our research.
OCBE has a central role in INTEGREAT, The Norwegian Centre for Knowledge-driven Machine Learning (ML), a center of excellence funded by the Research Council of Norway. The center is in operation from 2023 to 2033 and will fund more than 60 PhD and postdoc positions. INTEGREAT develops theories, methods, models and algorithms that integrate general and domain-specific knowledge with data, extending the data-centric paradigm of ML. Applicants for this position will be especially interested in pursuing their research within INTEGREAT, for example by taking a role as principal investigator in the center.
Role summary
The successful candidate will initiate, perform and lead research, supervise PhD candidates, postdocs and researchers, participate in and further develop our teaching and statistical advising, and carry out administrative duties in accordance with the needs of OCBE and the Institute.
You will have full operational responsibility for your research and funding. You will apply for funding, develop and manage an independent scientific programme, preferably in collaboration with other colleagues at OCBE and INTEGREAT at UiO, in Norway and internationally. You will be proactive in making your research known to the public. When relevant, you should consider commercial exploitation of discoveries and other forms of societal impact. You will contribute to the strategic research leadership of OCBE. As an Associate Professor, you will have the opportunity to apply for promotion to full Professor at a later stage.
Teaching, statistical advising and student supervision will amount to approximately half of the workload. The role holder will be an excellent teacher who motivates students and leads them pedagogically. The UiO has programmes that recognise excellence in teaching. As statistical adviser, you will be able to recommend state-of-the-art approaches and tools to researchers in the biomedical field who require support. Some of the advising work will lead to co-authorship.
The location of OCBE and Integreat are on the campus of UiO in Oslo.
More about the position here.
Qualification requirements
- Doctoral degree or equivalent qualifications in biostatistics, statistics, machine learning, mathematics, data science, computer science or other relevant field.
- Expertise in statistical/ probabilistic machine learning, together with a strong interest in applications in medicine, including basic medical research, clinical medicine, epidemiology and/or public health.
- Applicants must show promise to become leading academics, with a strong research record, as judged by the strength of their
- peer-reviewed scientific publications and must be an independent researcher in their field.
- Applicants must have some experience in supervision of students.
- Applicants must have some experience in leading research. Experience in managing a research group is an advantage but not necessary.
- Applicants must have some experience in applying for scientific funding.
- Applicants must provide a plan for research development and for acquiring external funding.
- Excellent communication skills in written and oral English are a prerequisite.
Additional desirable qualifications
- Experience with biostatistical advising and formal pedagogical competence will count positively. Applicants who do not have documented basic university pedagogical competence must acquire this within two years from appointment.
- Documentation of qualifications in public communication activities, management and administration will count positively.
Personal skills
- Strong interpersonal skills and the potential to create an attractive research environment will be emphasised.
- Ability to engage in active collaboration with student and colleagues, interdisciplinary and internationally.
- Strong administrative skills to manage projects and contribute to the common workload of OCBE.
