Stellenangebot
PhD position at HEC Lausanne
UNIL is a leading international teaching and research institution,
with over 5,000 employees and 17,000 students split between its
Dorigny campus, CHUV and Epalinges. The Department of Actuarial
Science of the Faculty of Business and Economics will be the host
institution for this SNSF Doctoral Student in Actuarial science.
THE DEPARTMENT OF ACTUARIAL SCIENCE OF HEC LAUSANNE IS LOOKING FOR A SNSF DOCTORAL STUDENT
The candidate for this opening could be a holder of a master's degree in Actuarial Sciences or Economics with possible specializations such as Finance or Information Systems. It could also be a holder of an engineering master's degree in Statistics, Computer Science or Data Science. In any case, the candidate is expected to have strong knowledge in Python or R and of Machine Learning techniques such as Random Forests and Neural Network estimations (CNN, RNN, LSTM, Transformer) using off-the-shelf packages such as Pytorch and scikit-learn.
DETAILS
Starting date: February 1, 2024 (or to be agreed)
Contract duration: 1 year, renewable 3 years, maximum 4 years
Activity rate: 100%
Workplace: Lausanne Dorigny, Extranef building
Salary: according to the wage scale for SNSF Doctoral Students: 1st year CHF 47699, 2nd year CHF 49220, 3rd and 4th year CHF 50741 + possibility of Indemnity I (CHF 761.-/month) and Indemnity II (CHF 507/month) (in exchange of teaching assignments including exam supervision, administrative technical and research support for the faculty and/or department)
Supervisors: Prof. Séverine Arnold with co-supervsion by Prof. Michael Rockinger
DESCRIPTION OF OPENING
This is a Swiss National Science Foundation (SNSF) financed project with a specific topic: _Forecasting Mortality: Leveraging Cause-of-Death Data through Neural Network Techniques_. So far, mortality forecasting involved time-series techniques using historical mortality. There exists however data on the causes of death which can also be used as predictor. Also, over the past years, improved forecasting techniques allowing for non-linear structures using machine learning tools have been developed. The aim of this thesis is to bring together all those components to understand the improvements that can be gained by their combination. This research is most important for insurance companies and public health organizations to gain better understanding of the causes of mortality. As such, the project is of high social utility. A death due to a car accident does not have the same social implications as death due to old age.
Institutions involved:
Our future PhD student will be working in an international team of researchers involving professors from the University of Lausanne (UNIL, Switzerland) and the University of New South Wales (UNSW, Sydney, Australia). The position will be mainly based in Lausanne (Switzerland), but stays in Sydney are also planned for the student. UNSW Sydney is one of Australia’s leading research and teaching universities. The school of Risk and Actuarial Studies is at the forefront of research in actuarial science, risk analytics, pensions and population ageing, ranked 1st in The UNL Global Research Rankings of Actuarial Science and Risk Management & InsuranceTM.
YOUR QUALIFICATIONS
Knowledge of Machine Learning and Python/R programming is a key requirement. Additional knowledge of Statistics and actuarial science is expected.
For admission you must hold a Master of Science (MSc) in any of the following fields: Actuarial Science, Economics, Statistics, Computer Science, Mathematics or similar.
Desire to deepen the knowledge in actuarial science through research and to write a doctoral thesis in actuarial science.
Fluency in English. Basic understanding of French is a plus.
Ability to work in a team and good communication skills.
WHAT THE POSITION OFFERS YOU
We offer a stimulating working environment in an international, diversified and dynamic research team.
CONTACT FOR FURTHER INFORMATION
Please contact the Department of Actuarial Science (DSA) of HEC/UNIL: catherine.lombard@unil.ch
YOUR APPLICATION
Only applications through this website will be accepted.
Application material:
Letter of motivation and CV.
Copies of university diplomas and degrees; transcripts (indicating marks/grades achieved).
An example of a research project, if available (e.g. master thesis, seminar work, etc).
Application deadline: July 31, 2023
ADDITIONAL INFORMATION
_UNIL is committed to equal opportunities and diversity._
https://career5.successfactors.eu/career?company=universitdP&site=VjItZy84VGQ5U1B5c09CRGlJeTlzUHdlZz09&career_job_req_id=20925&career_ns=job_listing&navBarLevel=JOB_SEARCH
_UNIL supports early career researchers._
https://unil.ch/graduatecampus/en/home.html
Apply to this job now...
https://www.unil.ch/egalite/en/home.html
THE DEPARTMENT OF ACTUARIAL SCIENCE OF HEC LAUSANNE IS LOOKING FOR A SNSF DOCTORAL STUDENT
The candidate for this opening could be a holder of a master's degree in Actuarial Sciences or Economics with possible specializations such as Finance or Information Systems. It could also be a holder of an engineering master's degree in Statistics, Computer Science or Data Science. In any case, the candidate is expected to have strong knowledge in Python or R and of Machine Learning techniques such as Random Forests and Neural Network estimations (CNN, RNN, LSTM, Transformer) using off-the-shelf packages such as Pytorch and scikit-learn.
DETAILS
Starting date: February 1, 2024 (or to be agreed)
Contract duration: 1 year, renewable 3 years, maximum 4 years
Activity rate: 100%
Workplace: Lausanne Dorigny, Extranef building
Salary: according to the wage scale for SNSF Doctoral Students: 1st year CHF 47699, 2nd year CHF 49220, 3rd and 4th year CHF 50741 + possibility of Indemnity I (CHF 761.-/month) and Indemnity II (CHF 507/month) (in exchange of teaching assignments including exam supervision, administrative technical and research support for the faculty and/or department)
Supervisors: Prof. Séverine Arnold with co-supervsion by Prof. Michael Rockinger
DESCRIPTION OF OPENING
This is a Swiss National Science Foundation (SNSF) financed project with a specific topic: _Forecasting Mortality: Leveraging Cause-of-Death Data through Neural Network Techniques_. So far, mortality forecasting involved time-series techniques using historical mortality. There exists however data on the causes of death which can also be used as predictor. Also, over the past years, improved forecasting techniques allowing for non-linear structures using machine learning tools have been developed. The aim of this thesis is to bring together all those components to understand the improvements that can be gained by their combination. This research is most important for insurance companies and public health organizations to gain better understanding of the causes of mortality. As such, the project is of high social utility. A death due to a car accident does not have the same social implications as death due to old age.
Institutions involved:
Our future PhD student will be working in an international team of researchers involving professors from the University of Lausanne (UNIL, Switzerland) and the University of New South Wales (UNSW, Sydney, Australia). The position will be mainly based in Lausanne (Switzerland), but stays in Sydney are also planned for the student. UNSW Sydney is one of Australia’s leading research and teaching universities. The school of Risk and Actuarial Studies is at the forefront of research in actuarial science, risk analytics, pensions and population ageing, ranked 1st in The UNL Global Research Rankings of Actuarial Science and Risk Management & InsuranceTM.
YOUR QUALIFICATIONS
Knowledge of Machine Learning and Python/R programming is a key requirement. Additional knowledge of Statistics and actuarial science is expected.
For admission you must hold a Master of Science (MSc) in any of the following fields: Actuarial Science, Economics, Statistics, Computer Science, Mathematics or similar.
Desire to deepen the knowledge in actuarial science through research and to write a doctoral thesis in actuarial science.
Fluency in English. Basic understanding of French is a plus.
Ability to work in a team and good communication skills.
WHAT THE POSITION OFFERS YOU
We offer a stimulating working environment in an international, diversified and dynamic research team.
CONTACT FOR FURTHER INFORMATION
Please contact the Department of Actuarial Science (DSA) of HEC/UNIL: catherine.lombard@unil.ch
YOUR APPLICATION
Only applications through this website will be accepted.
Application material:
Letter of motivation and CV.
Copies of university diplomas and degrees; transcripts (indicating marks/grades achieved).
An example of a research project, if available (e.g. master thesis, seminar work, etc).
Application deadline: July 31, 2023
ADDITIONAL INFORMATION
_UNIL is committed to equal opportunities and diversity._
https://career5.successfactors.eu/career?company=universitdP&site=VjItZy84VGQ5U1B5c09CRGlJeTlzUHdlZz09&career_job_req_id=20925&career_ns=job_listing&navBarLevel=JOB_SEARCH
_UNIL supports early career researchers._
https://unil.ch/graduatecampus/en/home.html
Apply to this job now...
https://www.unil.ch/egalite/en/home.html