sensing sensor configurations
Ladar is now looking for Phd student to assist us in our Randamp;D
project. The successful candidate will participate in our ongoing
multi-year project and have an opportunity to do relevant scientific
research within an industrial context and to collaborate with a broad
group of international scientists, universities, business partners and
shipping industry. The current PhD position will focus on met-ocean
parameter measurement from multiple remote sensing sensor
configurations.
PROJECT OBJECTIVES:
FUTURE APPLICATIONS IN OCEAN AND MARITIME SERVICES WILL REQUIRE THE
USE OF MULTIPLE SENSOR CONFIGURATIONS AND DATA ANALYSIS FOR THE
CHARACTERISATION OF THE MARITIME ENVIRONMENT AND METOCEAN PARAMETERS.
THESE SENSORS INCLUDE SATELLITE REMOTE SENSING SYSTEMS, SHIP-BASED
SENSORS, COASTAL RADARS, IN-SITU SENSORS, ETC.
THIS PHD POSITION FOCUSES ON THE COLLECTIVE USE OF THESE MULTIPLE
SENSORS FOR DERIVATION OF PRIMARY MET-OCEAN PARAMETERS OF WINDS,
WAVES, AND CURRENTS. THE WORK WILL INVOLVE INGESTION OF MEASUREMENTS
FROM DIFFERENT SENSORS, AND APPLICATION OF GEOPHYSICAL, EMPIRICAL,
COMPUTATIONAL ALGORITHMS FOR DERIVING THE BEST AND MOST SUITABLE
METOCEAN PARAMETERS. THIS WILL ALSO INVOLVE ANALYSIS OF THE ACCURACY
AND SUITABILITY OF DIFFERENT SENSORS IN DIFFERENT METOCEAN CONDITIONS
AND REGIONS.
THE CANDIDATE IS EXPECTED TO LEARN, CUSTOMIZE, AND APPLY THE
TECHNIQUES OF MACHINE LEARNING, DEEP LEARNING AND ARTIFICIAL
INTELLIGENCE TO THE INPUT DATASETS FOR DATA REFINEMENT, DATA
SELECTION, AND MET-OCEAN PARAMETER DERIVATION. THE MACHINE
LEARNING-BASED METHODS ARE EXPECTED TO BE SET UP TO INTEGRATE MORE
DATA FEEDS IN THE FUTURE AS WELL. THE CANDIDATE MAY ALSO BE NEEDED TO
PROVIDE SUPPORT IN PREPARATION AND EXECUTION OF TEST CAMPAIGNS AND
ERROR ANALYSIS.
THE QUALITY OF METOCEAN MEASUREMENTS IS KNOWN TO BE HIGH FOR IN-SITU
MEASUREMENTS, WHILE REMOTE SENSING MEASUREMENTS OFTEN REQUIRE
CALIBRATION AND IN GENERAL HAVE LESS ACCURACY THAN IN-SITU
MEASUREMENTS. HOWEVER, REMOTE SENSING MEASUREMENTS OFFER THE ADVANTAGE
OF SPATIAL / GRID MEASUREMENTS. WEATHER FORECASTS ARE REASONABLY
ACCURATE FOR THE FIRST **APPLY ON THE WEBSITE** DAYS, BUT THEIR
QUALITY AND USABILITY DETERIORATE AS THEY EXTEND OUT FURTHER IN TIME,
AND ALSO VARIES FROM LOCATION TO LOCATION. THIS DATA HIERARCHY NEEDS
TO BE CONNECTED THROUGH MACHINE LEARNING AND ASSOCIATED ALGORITHMS IN
A MANNER THAT THE ADVANTAGES OF ONE TYPE OF OBSERVATIONS CAN BE
CARRIED OVER TO THE OTHER TYPES OF OBSERVATIONS, TO MAKE THEM
COLLECTIVELY MORE USEFUL FOR SPECIFIC MARITIME APPLICATIONS.
REQUIREMENTS:
PREREQUISITES FOR THE POSITION ARE GOOD WORKING KNOWLEDGE AND
QUALIFICATIONS IN AT LEAST TWO OF THE FOLLOWING TOPICS: OPTICAL REMOTE
SENSING METHODS, RADAR REMOTE SENSING METHODS, SCIENTIFIC PROGRAMMING,
OCEANOGRAPHICAL MEASUREMENT AND MATHEMATICAL MODELLING, DATA FUSION,
MACHINE LEARNING. IN ADDITION, THE CANDIDATE MUST HAVE OPTIMISATION
BACKGROUND (PREFERABLY RELATED TO THE MOST EFFECTIVE USE OF MET-OCEAN
DATA).
EXPECTED RESULTS:
1) MACHINE-LEARNING BASED METHODOLOGY FOR DERIVATION OF MET-OCEAN
PARAMETERS FROM DIVERSE SET OF DATA FEEDS FROM DIFFERENT TYPES OF
SENSORS, ALONG WITH PARAMETER ACCURACY
2) A DESCRIPTION OF A PERFORMANCE INDEX OR SIMILAR QUANTITATIVE
PARAMETER TO RATE DIFFERENT SENSOR / DATA FEEDS FOR METOCEAN PARAMETER
DERIVATION IN DIFFERENT PHYSICAL CONDITIONS, SUCH AS SEASON, TIME OF
YEAR, SEA STATE, ETC.
3) ANALYSIS AND EXPLANATION OF THE ERRORS AND USABILITY ASSOCIATED
WITH DIFFERENT TYPES OF INPUT DATASETS, AND ALSO THE IMPROVEMENTS IN
THEIR ERRORS AND USABILITY AFTER THE APPLICATION OF DEVELOPED
METHODOLOGY DURING THE RESEARCH
4) RESULTS TO BE STATISTICALLY SIGNIFICANT, BASED ON UTILIZATION OF
LARGE AND DIVERSE INPUT DATASETS
WE OFFER EMPLOYEES A DYNAMIC AND COLLABORATIVE, TEAM-ORIENTED AND
INTERNATIONAL ENVIRONMENT WITH AN EXCELLENT WAGE AND BENEFIT PACKAGE
AS WELL AS THE FREEDOM TO CREATE YOUR OWN WORK-LIFE BALANCE.
OUR COMPANY OPERATES IN A TOP-TIER STATE-OF-THE-ART ENVIRONMENT AND
PROVIDES THE OPPORTUNITY TO WORK WITH AND DEVELOP ADVANCED
TECHNOLOGIES. OUR COMPANY IS CONSTANTLY GROWING AND IS COMMITTED TO
BUILDING A CULTURALLY DIVERSE AND INTERNATIONALLY PRESENT WORKFORCE.
THE COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER AND ALL QUALIFIED
APPLICANTS WILL RECEIVE CONSIDERATION FOR EMPLOYMENT WITHOUT REGARD TO
RACE, COLOR, RELIGION, SEX, NATIONAL ORIGIN, SEXUAL ORIENTATION,
GENDER IDENTITY, DISABILITY STATUS, PROTECTED VETERAN STATUS, OR ANY
OTHER CHARACTERISTIC PROTECTED BY LAW.
PLEASE FILL THE FOLLOWING FORM TO APPLY:
Your Full Name
Your Email
Your Motivational Message
YOUR CV
If there is any problem please send us your application by email with
the subject: Job Application, your CV and a motivational letter.
Email address: (Please contact us using the "Apply for this Job
Posting" box below)
Position: Phd Met-ocean parameter measurement from multiple remote
sensing sensor configurations
Ladar is now looking for Phd student to assist us in our Randamp;D
project. The successful candidate will participate in our ongoing
multi-year project and have an opportunity to do relevant scientific
research within an industrial context and to collaborate with a broad
group of international scientists, universities, business partners and
shipping industry. The current PhD position will focus on met-ocean
parameter measurement from multiple remote sensing sensor
configurations.
PROJECT OBJECTIVES:
FUTURE APPLICATIONS IN OCEAN AND MARITIME SERVICES WILL REQUIRE THE
USE OF MULTIPLE SENSOR CONFIGURATIONS AND DATA ANALYSIS FOR THE
CHARACTERISATION OF THE MARITIME ENVIRONMENT AND METOCEAN PARAMETERS.
THESE SENSORS INCLUDE SATELLITE REMOTE SENSING SYSTEMS, SHIP-BASED
SENSORS, COASTAL RADARS, IN-SITU SENSORS, ETC.
THIS PHD POSITION FOCUSES ON THE COLLECTIVE USE OF THESE MULTIPLE
SENSORS FOR DERIVATION OF PRIMARY MET-OCEAN PARAMETERS OF WINDS,
WAVES, AND CURRENTS. THE WORK WILL INVOLVE INGESTION OF MEASUREMENTS
FROM DIFFERENT SENSORS, AND APPLICATION OF GEOPHYSICAL, EMPIRICAL,
COMPUTATIONAL ALGORITHMS FOR DERIVING THE BEST AND MOST SUITABLE
METOCEAN PARAMETERS. THIS WILL ALSO INVOLVE ANALYSIS OF THE ACCURACY
AND SUITABILITY OF DIFFERENT SENSORS IN DIFFERENT METOCEAN CONDITIONS
AND REGIONS.
THE CANDIDATE IS EXPECTED TO LEARN, CUSTOMIZE, AND APPLY THE
TECHNIQUES OF MACHINE LEARNING, DEEP LEARNING AND ARTIFICIAL
INTELLIGENCE TO THE INPUT DATASETS FOR DATA REFINEMENT, DATA
SELECTION, AND MET-OCEAN PARAMETER DERIVATION. THE MACHINE
LEARNING-BASED METHODS ARE EXPECTED TO BE SET UP TO INTEGRATE MORE
DATA FEEDS IN THE FUTURE AS WELL. THE CANDIDATE MAY ALSO BE NEEDED TO
PROVIDE SUPPORT IN PREPARATION AND EXECUTION OF TEST CAMPAIGNS AND
ERROR ANALYSIS.
THE QUALITY OF METOCEAN MEASUREMENTS IS KNOWN TO BE HIGH FOR IN-SITU
MEASUREMENTS, WHILE REMOTE SENSING MEASUREMENTS OFTEN REQUIRE
CALIBRATION AND IN GENERAL HAVE LESS ACCURACY THAN IN-SITU
MEASUREMENTS. HOWEVER, REMOTE SENSING MEASUREMENTS OFFER THE ADVANTAGE
OF SPATIAL / GRID MEASUREMENTS. WEATHER FORECASTS ARE REASONABLY
ACCURATE FOR THE FIRST **APPLY ON THE WEBSITE** DAYS, BUT THEIR
QUALITY AND USABILITY DETERIORATE AS THEY EXTEND OUT FURTHER IN TIME,
AND ALSO VARIES FROM LOCATION TO LOCATION. THIS DATA HIERARCHY NEEDS
TO BE CONNECTED THROUGH MACHINE LEARNING AND ASSOCIATED ALGORITHMS IN
A MANNER THAT THE ADVANTAGES OF ONE TYPE OF OBSERVATIONS CAN BE
CARRIED OVER TO THE OTHER TYPES OF OBSERVATIONS, TO MAKE THEM
COLLECTIVELY MORE USEFUL FOR SPECIFIC MARITIME APPLICATIONS.
REQUIREMENTS:
PREREQUISITES FOR THE POSITION ARE GOOD WORKING KNOWLEDGE AND
QUALIFICATIONS IN AT LEAST TWO OF THE FOLLOWING TOPICS: OPTICAL REMOTE
SENSING METHODS, RADAR REMOTE SENSING METHODS, SCIENTIFIC PROGRAMMING,
OCEANOGRAPHICAL MEASUREMENT AND MATHEMATICAL MODELLING, DATA FUSION,
MACHINE LEARNING. IN ADDITION, THE CANDIDATE MUST HAVE OPTIMISATION
BACKGROUND (PREFERABLY RELATED TO THE MOST EFFECTIVE USE OF MET-OCEAN
DATA).
EXPECTED RESULTS:
1) MACHINE-LEARNING BASED METHODOLOGY FOR DERIVATION OF MET-OCEAN
PARAMETERS FROM DIVERSE SET OF DATA FEEDS FROM DIFFERENT TYPES OF
SENSORS, ALONG WITH PARAMETER ACCURACY
2) A DESCRIPTION OF A PERFORMANCE INDEX OR SIMILAR QUANTITATIVE
PARAMETER TO RATE DIFFERENT SENSOR / DATA FEEDS FOR METOCEAN PARAMETER
DERIVATION IN DIFFERENT PHYSICAL CONDITIONS, SUCH AS SEASON, TIME OF
YEAR, SEA STATE, ETC.
3) ANALYSIS AND EXPLANATION OF THE ERRORS AND USABILITY ASSOCIATED
WITH DIFFERENT TYPES OF INPUT DATASETS, AND ALSO THE IMPROVEMENTS IN
THEIR ERRORS AND USABILITY AFTER THE APPLICATION OF DEVELOPED
METHODOLOGY DURING THE RESEARCH
4) RESULTS TO BE STATISTICALLY SIGNIFICANT, BASED ON UTILIZATION OF
LARGE AND DIVERSE INPUT DATASETS
WE OFFER EMPLOYEES A DYNAMIC AND COLLABORATIVE, TEAM-ORIENTED AND
INTERNATIONAL ENVIRONMENT WITH AN EXCELLENT WAGE AND BENEFIT PACKAGE
AS WELL AS THE FREEDOM TO CREATE YOUR OWN WORK-LIFE BALANCE.
OUR COMPANY OPERATES IN A TOP-TIER STATE-OF-THE-ART ENVIRONMENT AND
PROVIDES THE OPPORTUNITY TO WORK WITH AND DEVELOP ADVANCED
TECHNOLOGIES. OUR COMPANY IS CONSTANTLY GROWING AND IS COMMITTED TO
BUILDING A CULTURALLY DIVERSE AND INTERNATIONALLY PRESENT WORKFORCE.
THE COMPANY IS AN EQUAL OPPORTUNITY EMPLOYER AND ALL QUALIFIED
APPLICANTS WILL RECEIVE CONSIDERATION FOR EMPLOYMENT WITHOUT REGARD TO
RACE, COLOR, RELIGION, SEX, NATIONAL ORIGIN, SEXUAL ORIENTATION,
GENDER IDENTITY, DISABILITY STATUS, PROTECTED VETERAN STATUS, OR ANY
OTHER CHARACTERISTIC PROTECTED BY LAW.
PLEASE FILL THE FOLLOWING FORM TO APPLY:
Your Full Name
Your Email
Your Motivational Message
YOUR CV
If there is any problem please send us your application by email with
the subject: Job Application, your CV and a motivational letter.
Email address: (Please contact us using the "Apply for this Job
Posting" box below)
We need : English (Good)
Type: Permanent
Payment:
Category: Others
