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Stillingstittel:
Associate Professor in Machine Learning - two positions

Stillingsbeskrivelse:

Jobbnorge ID: 172639

Job abstractJV_description

Two permanent positions as Associate Professor are available at the Department of Informatics within the field of machine learning (ML).

The department seeks potential scientific leaders with clear research visions, educational and administrative skills and abilities to establish and lead research projects, who will strengthen our research and education.

About the position

The main subject areas of ML-driven research within the department are image analysis, language technology, robotics and intelligent systems, and bioinformatics. We expect candidates to show a strong record of conducting research in ML and with a specialization within one or more of these subject areas, in terms of both research experience and teaching qualifications. The position will be located with one of the relevant research groups within the department; DSB, LTG, ROBIN, or BMI. Candidates are expected to initiate, lead and carry out original research within ML and to acquire external funding for new research projects. Candidates will also take part in teaching and developing various machine learning courses within the department.

Up to 50% of the working time will be devoted to teaching (including supervision of students), teaching related activities, and administrative tasks. The department offers classes at the bachelor, master and PhD-level. Lectures and tuition are given in English and Norwegian (at the bachelor level).

Qualification requirements

The candidates must have a PhD in a relevant area and have actively conducted research in machine learning after the reception of the doctorate, demonstrating a strong record within the field. The candidate must document scientific achievements and experience in education and research leadership.

The candidates must clearly state which subject area(s) and research group(s) that the application targets. Competence and research interests in more than one of the relevant subject areas will be considered an advantage. This should then also be reflected in the research plan submitted as part of the application.

Assessment criteria:

• Candidates must have a PhD in a relevant area for the position and a scientific track record that confirms his or her capacity to take up new and challenging issues.
• Candidates must have a strong research background in machine learning, including applications of ML to at least one of the research areas of computer vision, language technology, robotics and intelligent systems, or bioinformatics.
• A strong record of publications relevant to the area is required. Candidates must have international publications in acknowledged publication channels. In the assessment of publications, originality, quality and scope will be emphasized.
• Research output from the previous 5 years will be given particular weight.
• Since the field of machine learning is rapidly evolving, versatility and a proven ability to adapt the research focus is considered an advantage.
• Candidates should also be able to lead, conduct and collaborate in research projects. A strong track record in academic and administrative leadership is an advantage, as well as experience in the acquisition of research grants.
• Candidates will be assessed with respect to all relevant documented pedagogical experience and skills.
• Candidates must have teaching experience in machine learning and have a commitment to engage in undergraduate and graduate education and in mentoring and advising master and doctoral students.

Additional group-specific criteria:

• For candidates applying towards the Language Technology Group, experience with neural methods is a requirement and will be given weight in the assessment.
• For candidates applying towards the Digital Signal Processing and Image Analysis Group, solid experience with convolutional networks for image analysis, in addition to a background in traditional image analysis is a requirement and will be given weight in the assessment.

The successful candidates should have an international profile with respect to the above criteria. The candidates for this position will be selected based on excellence and fit with the research profile of the relevant research group(s).

Interviews will be part of the appointment process, along with a trial lecture.

We offer

• salary NOK 640 200- 741 300 per annum depending on qualifications in position as Associate professor (position code 1011)
• a professionally stimulating working environment
• attractive welfare benefits and a generous pension agreement, in addition to Oslo's family-friendly environment with its rich opportunities for culture and outdoor activities
• the opportunity to apply for promotion to full professorship at a later stage

How to apply

The application must include:

• Application letter
• A research position paper (1-4 pages) describing the applicant's vision and ambitions for the nearest future, including a abstractJV_description of which subject area(s) and research group(s) the applicant considers as most relevant for his/her research. The research plan must explicitly address how the applicant envisions that his or her research will contribute to the specified group(s).
• Detailed CV (including complete list of education, positions, pedagogical experience, administrative experience, project acquisition and coordination experience, funding and awards, and other qualifying activities).
• Copies of educational certificates, PhD diploma, transcript of records and letters of recommendation.
• A complete list of publications and academic merits and awards (if not included in the CV).
• Full text of up to 10 selected publications the applicant wishes to include in the evaluation.
• A document discussing the importance, interrelation, and relevance of the selected papers for this position.
• Listing of teaching experience as well as work on developing/revising/renewing study plans and the design of courses.
• Documentation of teaching qualifications and supervision of Master and PhD students, and up to a page describing teaching philosophy.
• Description of dissemination activities beyond scientific publications.
• List of 3 reference persons (name, relation to candidate, e-mail and phone number).

The application with attachments must be delivered in our electronic recruiting system. Please note that all documents should be in English (or a Scandinavian language).

Formal regulations

The successful candidate who at the time of appointment cannotdocument basic teaching qualifications will be required to obtain such qualifications within a two-year period.

The successful candidate must demonstrate mastery of both English and one of the Scandinavian languages as working languages. If an appointee is not fluent in a Scandinavian language, the appointee will be expected within a two-year period to learn sufficient Norwegian to be able to participate actively in all functions the position may involve.

Please see the rules for Appointments to Professorships and Associate Professorships and Rules for the assessment and weighting of pedagogical competence.

According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results etc.

The University of Oslo aims to achieve a balanced gender composition in the workforce and to recruit people with ethnic minority backgrounds.

Contactinformation

Associate Professor Erik Velldal, email: erikve (at) ifi.uio.no, tel. +47 22840119

Professor Anne Schistad Solberg, email: anne (at) ifi.uio.no, tel. +47 22852435

For questions regarding the recruitment system, please contact HR Adviser Torunn Standal Guttormsen, phone:+47 22854272, email:t.s.guttormsen (at) mn.uio.no

Se annonsen og søk på stillingen www.jobbnorge.no

PAM

numberOfPosts: 1

jobCategoriesCodes_0: http://data.europa.eu/esco/isco/C2310

abstractJV_contact_0: See jobabstractJV_description

contractTypeCodes_0: fulltime

Arbeidsgiver Navn: Universitetet i Oslo

source: NAV