PhD Fellowship in Theoretical and Experimental Neuroscience
About the position
The work carried out in this project is partially financed by the Strategic initiative for Health at NTNU and connected to the Centre of Excellence of the Research Council of Norway, "Centre for Neural Computation" at the Kavli institute. Successful candidates will be offered a three-year position. One or both candidates may be offered a twelve months extension as a teaching assistant. The work place will be Trondheim.
Main duties and responsibilities
The overall project will involve the development and integration of four experimental and theoretical tools: 1) Microdissection of live neurons from relevant brain regions that will be cultured into Alzheimer’s disease-relevant neural networks in an in-vitro preparation, 2) selective genetic manipulation of neurons, 3) electrophysiological recording and 4) characterization of the population activity of the cultured neurons and comparisons between these and controls.
The PhD student in Neuroscience will work in the group of Professor Menno Witter and be co-supervised by Dr. Asgeir Kobro-Flatmoen. The role of the student will be to microdissect live neurons and successfully harvest these for transfer into an in-vitro experimental setup. This setup will enable the culturing of neurons into an Alzheimer-relevant neuronal network in order to test fundamental hypotheses about the origin and spread of neuronal dysfunction in the context of Alzheimer’s disease. Data generated from this approach will involve electrophysiological recordings of neuronal activity of such neuronal cultures, which will be analyzed in collaboration with the PhD student recruited by Associate Professor Benjamin Dunn (see below).
The PhD student in Mathematics will work in the group of Associate Professor Benjamin Dunn on the development of a framework to characterize and compare population neural activity. The analysis of the network dynamics will build on principles of state space representation using statistical/machine learning and topological data analysis methods.
For the position in the Kavli Institute for Systems Neuroscience / Centre for Neural Computation, the applicant must have a master’s degree in Neuroscience or comparable competence.
For the position in the Mathematics department, the applicant must have a master’s degree in Statistics, Mathematics or comparable competence.
Both students must also satisfy the requirement for entering the PhD programme at NTNU; please see http://www.ntnu.edu/ie/research/phd (for the position in the Mathematics department) and https://www.ntnu.edu/mh/phd (for the position in the Kavli Institute). The admission to PhD education at NTNU requires an average grade of A or B within a scale of A-E for passing grades (A best) for the last two years of the MSc, and C or higher for the BSc.
MSc students who expect to complete their master’s degree studies by summer 2019 are encouraged to apply.
Both students will work in an international environment where English is the common language for oral and written communication. Fluency in English is therefore required.
The appointment is to be made in accordance with the regulations in force concerning State Employees and Civil Servants and national guidelines for appointment as PhD, post doctor and research assistant.
In the evaluation of which candidate is best qualified, emphasis will be placed on education, experience and personal suitability, including motivation for the announced position.
For the position in experimental neuroscience, knowledge of fundamental brain anatomy and electrophysiological experience is an important additional selection criterion.
The following will be emphasized in the evaluation of the applications for the position in the Mathematics department: programming experience, knowledge of statistical/machine learning or topological data analysis methods, interest in working with neural data, communication and writing skills.
- exciting and stimulating tasks in a strong international academic environment
- an open and inclusive work environment with dedicated colleagues
- favourable terms in the Norwegian Public Service Pension Fund
- employee benefits
Salary and conditions
PhD candidates are remunerated in code 1017, and are normally remunerated at gross from NOK 449 400 per annum before tax. From the salary, 2% is deducted as a contribution to the Norwegian Public Service Pension Fund.
As a PhD candidate, you undertake to participate in an organized PhD programme during the employment period. In the case of Neuroscience that includes compulsory educational activities as organized by NTNU and the Norwegian Research school of Neuroscience NRSN, of which you must become a member; please see https://www.ntnu.edu/nrsn . A condition of appointment is that you are in fact qualified for admission to the PhD programme within three months.
Appointment takes place on the terms that apply to State employees at any time, and after the appointment you must assume that there may be changes in the area of work.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology. Candidates who by assessment of the application and attachment are seen to conflict with the criterias in the latter law will be prohibited from recruitment to NTNU. After the appointment you must assume that there may be changes in the area of work.
Working at NTNU
A good work environment is characterized by diversity. We encourage qualified candidates to apply, regardless of their gender, functional capacity or cultural background. Under the Freedom of Information Act (Offentleglova), information about the applicant may be made public even if the applicant has requested not to have their name entered on the list of applicants.
About the application:
The application must include the following:
- Information about education background and work experience.
- A short research statement explaining the experience and the interest of the candidate for the research topic, and describing the relevance of the candidate’s background to the research project (maximum 1 page).
- Any relevant publications. Joint work will only be considered provided that a short summary outlining the applicant's contributions is attached.
- Certified copies of relevant transcripts and diplomas. Candidates from universities outside Norway are kindly requested to send a Diploma Supplement or similar documentation, which describes in detail the program of study, the grading system, and the rights to further studies associated with the degree obtained.
- Contact information for at least two references.
- Documentation of proficiency in the English language (equivalent to a TOEFL score of 600 or more). In extraordinary circumstances, formal documentation of language skills can be relinquished. In such cases, the candidate’s language skills will be assessed in a personal interview.
Please submit your application electronically via jobbnorge.no . Preferably, the attachments should be submitted as a single file.
Please refer to the application number 2019/13636 when applying.
Application deadline: July 1st, 2019.
NTNU - knowledge for a better world
The Norwegian University of Science and Technology (NTNU) creates knowledge for a better world and solutions that can change everyday life.
Department of Mathematical Sciences
We are Norway’s largest university environment in mathematical sciences. The Department has a particular responsibility for all basis education in mathematical sciences for engineering and natural science students at NTNU. We focus on long-term basic research and applied research at a high international level.
Our aim is to meet the society’s needs for mathematical and statistical expertise in business and public administration as well as in the research and education sector. The Department of Mathematical Sciences is one of seven departments in the Faculty of Information Technology and Electrical Engineering .
Deadline 1. July 2019
Employer NTNU - Norwegian University of Science and Technology
Place of service Trondheim